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At least 595 records · Page 33

APPLICATION OF MATURITY MODELS FOR EVALUATING CYBERSECURITY PROGRAMS AT NUCLEAR AND RADIOLOGICAL FACILITIES

Maturity models can be used to provide government agencies, industry associations, and organizations operating nuclear facilities with the ability to quickly evaluate the maturity of their cybersecurity programs and identify areas to prioritize for improvement. The Cybersecurity Capability Maturity Model (C2M2) was developed by the U.S. Department of Energy to allow organizations in the energy sector to evaluate the programmatic capabilities of their cybersecurity programs in a consistent manner, communicate programmatic maturity information, prioritize cybersecurity investments in targeted areas of concern, and track how the maturity of their cybersecurity program evolves over time. The C2M2 is designed for use by any critical infrastructure organization regardless of ownership, structure, or size. The C2M2 can be easily fine-tuned to access the maturity of nuclear cybersecurity programs and their application at individual facilities. Built on a foundation of existing cybersecurity standards, frameworks, programs, and initiatives, the model features 10 security domains. Performance in each security domain is characterized using a structured set of cybersecurity practices that represent activities an organization can perform to improve cybersecurity in their domain. Each practice can be quickly evaluated as being either fully, largely, partially, or not implemented. Once practices are evaluated for each security domain, the model defines four maturity indicator levels that apply independently to each domain in the model. To earn a maturity level in a given domain, an organization must adequately perform all the practices for that maturity level and its predecessor level(s). A small assessment team can conduct a C2M2 assessment in a single day. A screening version of the C2M2 allows an initial look at the maturity of nuclear cybersecurity programs that could be completed in under an hour.

Cyber security, Nuclear security, maturity model↗

Economic viability of using thermal energy storage for flexible carbon capture on natural gas power plants

Fossil fuel-based power plants generate 80% of the electricity in the United States and provide a reliable generation source for both base and peak power demands. These plants are expected to adapt to changes in environmental policies that will require carbon management with carbon capture and storage (CCS) representing a possible solution. Current solvent-based CCS has a detrimental impact on a power plant's performance due to large heat loads required for carbon capture solvent regeneration. This parasitic load restricts the power plant's output and operation flexibility. Therefore, this study evaluates the feasibility of using thermal storage technologies for natural gas combined cycle (NGCC) power plants coupled with CCS to minimize the impact of solvent regeneration and enable the plant to operate at peak power output. Thermal storage can minimize the impact of CCS on the power plant by providing the heat load required for solvent regeneration during times of peak demand which will allow the plant to operate unrestricted and at full power. In total, fifteen unique thermal storage configurations were evaluated from three thermal storage categories: Brayton cycle heat pump, vapor compression heat pump, and heat recovery steam generator steam extraction for storage. The viability of these systems was determined by evaluating each configuration on thousands of real-world Locational Marginal Pricing (LMP) profiles from the New York Independent System Operator and California Independent System Operator electricity markets using a techno-economic analysis. Afterwards, results were compared to the performance of a base power plant (NGCC with CCS and no thermal storage) to determine the impact of thermal storage on power plant economics. Overall, six of the thermal storage configurations performed better than base CCS enabled power plant on between 11.5% and 38.7% of the LMP signals evaluated. The best performing configuration was a vapor compression heat pump that used flue gas as the working fluid and had both hot and cold thermal storage units. This configuration performed better than the base CCS power plant on 38.7% of the LMP profiles. The results of this study show thermal storage can mitigate the economic impact of carbon capture solvent regeneration on NGCC power plants. Discussion focuses on the impact of electricity pricing on the optimal thermal storage system, the advantages and disadvantages of the systems evaluated, and identifies limitations with the study.

25 ENERGY STORAGE↗

Combined TREAT-LOC & SATS Integral LOCA Experiment Plan

The Transient Reactor Test Facility (TREAT) loss-of-coolant (LOC) and highburnup (HBu) experiment series, along with the Severe Accident Test Station (SATS) HBu experiment series, are integral LOC accident (LOCA) experiments planned under the Department of Energy (DOE) Advanced Fuels Campaign (AFC) program, which aims to support burnup extension needs by addressing identified R&D priorities in order to achieve an improved understanding of fuel fragmentation, relocation, and dispersal (FFRD) of HBu fuel during LOCA events. Priorities have been identified by the Electric Power Research Institute (EPRI)’s Collaborative Research on Advanced Fuel Technologies (CRAFT) Fuel Performance and Testing Technical Experts Group (FPTTEG). The data produced under this plan will be used to further validate and confirm existing models and inform future R&D and model development. The experimental program was specifically developed to address data gaps and opportunities identified via detailed review of the existing public knowledge base on LOCA FFRD, as well as reviewing specific experimental development activities regarding prototypic LOCA conditions for light-water reactor (LWR) systems. The test program relies on a unique combination of in- and out-of-pile experimental approaches to provide a clear tieback to the existing integral and semi-integral LOCA experiment database, using state-of-the-art facilities. More importantly, the program will systematically investigate the impacts of prototypic HBu fuel/cladding thermomechanical behaviors under postulated LWR LOCA conditions not yet fully investigated. These conditions correspond with prototypic decay-energy heatup (DEH) and stored-energy heatup (SEH) conditions. First, TREAT’s unique capability will enable the first evaluation of the impact of SEH conditions on HBu fuels. The test program will emphasize the development of an improved mechanistic understanding of key phenomena through independent experimental systems, development of a database to support fuel performance modeling tools, world-leading advanced materials characterization, and the most advanced approach to in situ diagnostics ever deployed to evaluate FFRD. The results will represent a significant leap forward in evaluating prototypic conditions and novel data to support modeling development and validation, as well as to inform the technical basis for LOCA-induced FFRD.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Nuclear Structure and Decay Data for A=44 Isobars

Experimental nuclear spectroscopic data are evaluated for 12 known nuclides of mass number A=44 (Si, P, S, Cl, Ar, K, Ca, Sc, Ti, V, Cr, Mn). Detailed evaluated information are presented for each reaction and decay. Recommended values combining all available data are provided for all spectroscopic properties of each level, γ-ray, and decay radiation. No excited states have yet been identified in 44 Si, 44 P, 44 Cr, and 44 Mn. Information for excited states in 44 Cl and 44 V are limited. Nuclides of 44 S, 44 Ar and 44 K have been studied via only a few reactions and decays, while 44 Ca, 44 Sc and 44 Ti are the most investigated nuclides through various reactions and decays. Evaluators note that the half-life of the g.s. of 44 S has been measured independently, with fairly good statistics, in three references, most precise being 100 ms 1 by 2004Gr20, but this value is in disagreement with the values of 125.5 ms 25 and 119 ms 6 by 2022Tr03, and 123 ms 10 by 1995So03. We adopted the unweighted average of this discrepant dataset. Another outstanding issue is that of the β + -delayed proton decay of 44 Cr g.s. to 44 V, where the T=2, 0 + IAS state in 44 V is expected to be strongly populated by a superallowed β transition, but has not been definitely identified as discussed in detail by 2020Fu05. A detailed study of 44 Cr decay is required to unravel the status of the T=2, 0 + IAS state in 44 V. Furthermore, this work supersedes earlier ENSDF evaluations of A=44 by 2011Ch39 and 1999Ca45.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Global Assimilation of L-Band Brightness Temperature Observations from SMAP and SMOS into the Catchment Land Surface Model and Contribution to the Skill of Soil Moisture Estimates

The Soil Moisture Active Passive (SMAP) and Soil Moisture Ocean Salinity (SMOS) missions provide global observations of L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations at a resolution of ~40 km every 2-3 days. These observations have been available since 2015 from SMAP and since 2010 from SMOS.Soil moisture estimates from the separate assimilation of SMAP and SMOS Tb observations into land surface models were previously shown to improve over model-only estimates, thereby demonstrating the value of assimilating L-band Tb observations for soil moisture estimation. The assimilation experiments documented in the literature do not, however, establish whether the joint assimilation of SMAP and SMOS Tbs improves the skill of the resulting soil moisture estimates beyond what can be achieved with either set of observations alone. Moreover, because the published SMAP and SMOS results used different assimilation systems and configurations and applied different evaluation data and procedures, it is unclear whether the assimilation of SMAP-only or SMOS-only Tbs results in better soil moisture skill. In this presentation, we compare the results of three separate assimilation experiments for the period from April 2015 to present. The experiments utilize the SMAP Level-4 Soil Moisture (L4_SM) algorithm, which assimilates L-band Tb observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter. Specifically, the three experiments presented here assimilate (i) SMAP Tbs only, as in the L4_SM product, (ii) SMOS Tbs only, after interpolation of 40° incidence angle, and (iii) both SMAP and SMOS Tbs. In all other respects, the configuration of three experiments is identical, as is the validation of the output. Preliminary results suggest that the joint assimilation of SMAP and SMOS Tbs yields the most skillful soil moisture estimates when compared to independent in situ measurements. Moreover, the skill of the SMAP-only assimilation exceeds that of the SMOS-only assimilation. The presentation provides an in-depth evaluation of the skill of the assimilation estimates vs. independent in situ and satellite measurements and in terms of statistics of the observation-minus-forecast residuals and analysis increments.

Reichle, Rolf↗

Minnesota Solar Pathways: Illuminating Pathways to 10% Solar (Final Technical Report)

The Minnesota Solar Pathways project, funded in part by the Department of Energy’s Solar Energy Technologies Office, was a three-year project designed to explore least-risk, best-value strategies for meeting the State of Minnesota’s solar goals. As part of this aim, the Pathways Team modeled renewable generation costs, examined ways to streamline interconnection, and evaluated technologies that can increase solar hosting capacity on the distribution grid. Midway through the project period, the Pathways Team expanded the scope of study using the same modeling framework from the Minnesota Solar Potential Analysis to estimate and compare generation costs for high renewables penetration scenarios across the Midcontinent Independent System Operator (MISO) region. The analysis concludes that it can be cheaper to overbuild solar + wind and curtail surplus than to store all generation. In addition, the analysis of individual MISO subregions compared with the whole region highlights the opportunities of enabling market potential compared with impact of ongoing transmission constraints. Beyond the analysis of future scenarios, the partnerships initiated and supported through this project underscored the ongoing need for work with stakeholders to address key issues, particularly around siting, and leverage symbiotic strategies to meet state goals.

14 SOLAR ENERGY↗

Dynamical Downscaling of Earth System Model Data for Energy System Analysis

Assessing energy resources (e.g., solar, wind, and hydro) under future scenarios requires datasets with sufficient spatial and temporal detail to capture variability and extreme events. While global-scale Earth System Model (ESM) projections are widely used, their coarse resolution limits direct application to regional energy system analyses. Dynamical downscaling offers a robust approach to generate physically consistent, fine-scale datasets that better represent local atmospheric processes impacting energy resources. In this work, we present a two-stage approach for producing high-resolution historical and future projections over the contiguous United States (CONUS). First, we optimize the Weather Research and Forecasting (WRF) model configuration for energy-relevant variables - solar irradiance, wind speed, and precipitation - by conducting ERA5-driven simulations at 8-km and 28-km resolution. Multiple physics schemes and model configurations within the WRF are evaluated against observational datasets including the National Solar Radiation Database (NSRDB), the Parameter-elevation Regressions on Independent Slopes Model (PRISM), and the Stage IV multi-radar/multi-sensor precipitation product for the CONUS domain. Using the best-performing configuration, we dynamically downscale MPI-ESM1-2-HR simulations for 2000-2060 under SSP2-4.5 and SSP5-8.5 scenarios at 4-km spatial and hourly temporal resolution. This presentation will provide a comprehensive analysis of the results from multiple numerical experiments and high-resolution ESM projections. In addition, we will discuss potential applications of our high-resolution datasets within the energy sector and outline future research avenues dedicated to evaluating how extreme weather events influence system performance and resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Role of Cloud Contamination, Aerosol Layer Height and Aerosol Model in the Assessment of the OMI Near-UV Retrievals Over the Ocean

Retrievals of aerosol optical depth (AOD) at 388 nm over the ocean from the Ozone Monitoring Instrument (OMI) two-channel near-UV algorithm (OMAERUV) have been compared with independent AOD measurements. The analysis was carried out over the open ocean (OMI and MODerate-resolution Imaging Spectrometer (MODIS) AOD comparisons) and over coastal and island sites (OMI and AERONET, the AErosol RObotic NETwork). Additionally, a research version of the retrieval algorithm (using MODIS and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) information as constraints) was utilized to evaluate the sensitivity of the retrieval to different assumed aerosol properties. Overall, the comparison resulted in differences (OMI minus independent measurements) within the expected levels of uncertainty for the OMI AOD retrievals (0.1 for AOD less than 0.3, 30% for AOD greater than 0.3). Using examples from case studies with outliers, the reasons that led to the observed differences were examined with specific purpose to determine whether they are related to instrument limitations (i.e., pixel size, calibration) or algorithm assumptions (such as aerosol shape, aerosol height). The analysis confirms that OMAERUV does an adequate job at rejecting cloudy scenes within the instrument's capabilities. There is a residual cloud contamination in OMI pixels with quality flag 0 (the best conditions for aerosol retrieval according to the algorithm), resulting in a bias towards high AODs in OMAERUV. This bias is more pronounced at low concentrations of absorbing aerosols (AOD 388 nm approximately less than 0.5). For higher aerosol loadings, the bias remains within OMI's AOD uncertainties. In pixels where OMAERUV assigned a dust aerosol model, a fraction of them (less than 20 %) had retrieved AODs significantly lower than AERONET and MODIS AODs. In a case study, a detailed examination of the aerosol height from CALIOP and the AODs from MODIS, along with sensitivity tests, was carried out by varying the different assumed parameters in the retrieval (imaginary index of refraction, size distribution, aerosol height, particle shape). It was found that the spherical shape assumption for dust in the current retrieval is the main cause of the underestimate. In addition, it is demonstrated in an example how an incorrect assumption of the aerosol height can lead to an underestimate. Nevertheless, this is not as significant as the effect of particle shape. These findings will be incorporated in a future version of the retrieval algorithm.

aerosols↗

JACIE Radiometric Assessment of QuickBird Multispectral Imagery

Radiometric calibration of commercial imaging satellite products is required to ensure that science and application communities can place confidence in the imagery they use and can fully understand its properties. Inaccurate radiometric calibrations can lead to erroneous decisions and invalid conclusions and can limit intercomparisons with other systems. To address this calibration need, the NASA Stennis Space Center (SSC) Earth Science Applications (ESA) directorate,through the Joint Agency for Commercial Imagery Evaluation (JACIE) framework, established a commercial imaging satellite radiometric calibration team consisting of two groups: 1) NASA SSC ESA, supported by South Dakota State University, and 2) the University of Arizona Remote Sensing Group. The two groups determined the absolute radiometric calibration coefficients of the Digital Globe 4-band, 2.4-m QuickBird multispectral product covering the visible through near-infrared spectral region. For a 2-year period beginning in 2002, both groups employed some variant of a reflectance-based vicarious calibration approach, which required ground-based measurements coincident with QuickBird image acquisitions and radiative transfer calculations. The groups chose several study sites throughout the United States that covered nearly the entire dynamic range of the QuickBird sensor. QuickBird at-sensor radiance values were compared with those estimated by the two independent groups to determine the QuickBird sensor's radiometric accuracy. Approximately 20 at-sensor radiance estimates were vicariously determined each year. The estimates were combined to provide a high-precision radiometric gain calibration coefficient. The results of this evaluation provide the user community with an independent assessment of the QuickBird sensor's absolute calibration and stability over the 2-year period. While the techniques and method described reflect those developed at the NASA SSC, the results of both JACIE team groups are included in this paper.

Pagnutti, Mary↗

Taking Climate Model Evaluation to the Next Level

Earth system models are complex and represent a large number of processes, resulting in a persistent spread across climate projections for a given future scenario. Owing to different model performances against observations and the lack of independence among models, there is now evidence that giving equal weight to each available model projection is suboptimal. This Perspective discusses newly developed tools that facilitate a more rapid and comprehensive evaluation of model simulations with observations, process-based emergent constraints that are a promising way to focus evaluation on the observations most relevant to climate projections, and advanced methods for model weighting. These approaches are needed to distil the most credible information on regional climate changes, impacts, and risks for stakeholders and policy-makers.

Eyring, Veronika↗

Data for Creating Yellow Seed Camelina sativa with Enhanced Oil Accumulation by CRISPR-Mediated Disruption of Transparent Testa 8

Camelina ( Camelina sativa L.), a hexaploid member of the Brassicaceae family, is an emerging oilseed crop being developed to meet the increasing demand for plant oils as biofuel feedstocks. In other Brassicas, high oil content can be associated with a yellow seed phenotype, which is unknown for camelina. We sought to create yellow seed camelina using CRISPR/Cas9 technology to disrupt its Transparent Testa 8 (TT8) transcription factor genes and to evaluate the resulting seed phenotype. We identified three TT8 genes, one in each of the three camelina subgenomes, and obtained independent CsTT8 lines containing frameshift edits. Disruption of TT8 caused seed coat colour to change from brown to yellow reflecting their reduced flavonoid accumulation of up to 44%, and the loss of a well-organized seed coat mucilage layer. Transcriptomic analysis of CsTT8-edited seeds revealed significantly increased expression of the lipid-related transcription factors LEC1, LEC2, FUS3, and WRI1 and their downstream fatty acid synthesis-related targets. These changes caused metabolic remodelling with increased fatty acid synthesis rates and corresponding increases in total fatty acid (TFA) accumulation from 32.4% to as high as 38.0% of seed weight, and TAG yield by more than 21% without significant changes in starch or protein levels compared to parental line. These data highlight the effectiveness of CRISPR in creating novel enhanced-oil germplasm in camelina. The resulting lines may directly contribute to future net-zero carbon energy production or be combined with other traits to produce desired lipid-derived bioproducts at high yields.

Biofuels↗

Seasonal grassland productivity forecast for the U.S. Great Plains using Grass–Cast

Every spring, ranchers in the drought-prone U.S. Great Plains face the same difficult challenge —trying to estimate how much forage will be available for livestock to graze during the upcoming summer grazing season. To reduce this uncertainty in predicting forage availability, we developed an innovative new grassland productivity forecast system, named Grass-Cast, to provide science-informed estimates of growing season above ground net primary production (ANPP). Grass-Cast uses over 30 yr of historical data including weather and the satellite-derived normalized vegetation difference index (NDVI)—combined with ecosystem modeling and seasonal precipitation forecasts—to predict if rangelands in individual counties are likely to produce below-normal, near-normal, or above-normal amounts of grass biomass (lbs/ac). Grass-Cast also provides a view of rangeland productivity in the broader region, to assist in larger scale decision-making—such as where forage resources for grazing might be more plentiful if a rancher’s own region is at risk of drought. Grass-Cast is updated approximately every two weeks from April through July. Each Grass-Cast forecast provides three scenarios of ANPP for the upcoming growing season based on different precipitation outlooks. Near real-time 8-d NDVI can be used to supplement Grass-Cast in predicting cumulative growing season NDVI and ANPP starting in mid-April for the Southern Great Plains and mid-May to early June for the Central and Northern Great Plains. Here, we present the scientific basis and methods for Grass-Cast along with the county-level production forecasts from 2017 and 2018 for ten states in the U.S. Great Plains. The correlation between early growing season forecasts and the end-of growing season ANPP estimate is >50% by late May or early June. In a retrospective evaluation, we compared Grass-Cast end-of-growing season ANPP results to an independent dataset and found that the two agreed 69% of the time over a 20-yr period. Although some predictive tools exist for forecasting upcoming growing season conditions, none predict actual productivity for the entire Great Plains. The Grass-Cast system could be adapted to predict grassland ANPP outside of the Great Plains or to predict perennial biofuel grass production.

54 ENVIRONMENTAL SCIENCES↗

Simulation of Continental Shallow Cumulus Populations Using an Observation-Constrained Cloud-System Resolving Model

Continental shallow cumulus (ShCu) clouds observed on 30 August 2016 during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) field campaign are simulated by using an observation-constrained cloud-system resolving model. On this day, ShCu forms over Oklahoma and southern Kansas and some of these clouds transition to deeper, precipitating convection during the afternoon. We apply a four-dimensional ensemble-variational (4DEnVar) hybrid technique in the Community Gridpoint Statistical Interpolation (GSI) system to assimilate operational data sets and unique boundary layer measurements including a Raman lidar, radar wind profilers, radiosondes, and surface stations collected by the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) atmospheric observatory into the Weather Research and Forecasting (WRF) model to ascertain how improved environmental conditions can influence forecasts of ShCu populations and the transition to deeper convection. Independent observations from aircraft, satellite, as well as ARM's remote sensors are used to evaluate model performance in different aspects. Several model experiments are conducted to identify the impact of data assimilation (DA) on the prediction of clouds evolution. The analyses indicate that ShCu populations are more accurately reproduced after DA in terms of cloud initiation time and cloud base height, which can be attributed to an improved representation of the ambient meteorological conditions and the convective boundary layer. Extending the assimilation to 18 UTC (local noon) also improved the simulation of shallow-to-deep transitions of convective clouds.

54 ENVIRONMENTAL SCIENCES↗

The impacts of rising vapour pressure deficit in natural and managed ecosystems

Abstract An exponential rise in the atmospheric vapour pressure deficit (VPD) is among the most consequential impacts of climate change in terrestrial ecosystems. Rising VPD has negative and cascading effects on nearly all aspects of plant function including photosynthesis, water status, growth and survival. These responses are exacerbated by land–atmosphere interactions that couple VPD to soil water and govern the evolution of drought, affecting a range of ecosystem services including carbon uptake, biodiversity, the provisioning of water resources and crop yields. However, despite the global nature of this phenomenon, research on how to incorporate these impacts into resilient management regimes is largely in its infancy, due in part to the entanglement of VPD trends with those of other co‐evolving climate drivers. Here, we review the mechanistic bases of VPD impacts at a range of spatial scales, paying particular attention to the independent and interactive influence of VPD in the context of other environmental changes. We then evaluate the consequences of these impacts within key management contexts, including water resources, croplands, wildfire risk mitigation and management of natural grasslands and forests. We conclude with recommendations describing how management regimes could be altered to mitigate the otherwise highly deleterious consequences of rising VPD.

54 ENVIRONMENTAL SCIENCES↗

Buckling analysis of a missile interstage

The NASTRAN program was used to find the buckling location and the degradation factor due to a specified temperature field for an interstage of a typical three stage missile. The model was made up of 6332 independent degrees of freedom. This large size required the use of an IBM 370/195 for evaluation of the eigenvalues. The effect of elevated temperature was to lower the critical buckling load by 3%.

Dudley, D. P.↗

Analysis of stress-strain, fracture and ductility behavior of aluminum matrix composites containing discontinuous silicon carbide reinforcement

Mechanical properties and stress-strain behavior for several types of commercially fabricated aluminum matrix composites, containing up to 40 vol % discontinuous SiC whisker, nodule, or particulate reinforcement were evaluated. It was found that the elastic modulus of the composites was isotropic, to be independent of type of reinforcement, and to be controlled solely by the volume percentage of SiC reinforcement present. The yield/tensile strengths and ductility were controlled primarily by the matrix alloy and temper condition. Ductility decreased with increasing reinforcement content, however, the fracture strains observed were higher than those reported in the literature for this type of composite. This increase in fracture strain is attributed to cleaner matrix powder and increased mechanical working during fabrication. Conventional aluminum and titanium structural alloys were compared and have shown that the properties of these low cost, lightweight composites have good potential for application to aerospace structures.

Mcdanels, D. L.↗

Surface entropy of liquids via a direct Monte Carlo approach - Application to liquid Si

Two methods are presented for a direct Monte Carlo evaluation of the surface entropy S(s) of a liquid interacting by specified, volume-independent potentials. The first method is based on an application of the approach of Ferrenberg and Swendsen (1988, 1989) to Monte Carlo simulations at two different temperatures; it gives much more reliable results for S(s) in liquid Si than previous calculations based on numerical differentiation. The second method expresses the surface entropy directly as a canonical average at fixed temperature.

Wang, Z. Q.↗

Transport Canada aging aircraft activities

A description is given of recent initiatives undertaken in Canada to address the problems of aging passenger airplanes. In addition to participation in and support of U.S. aging aircraft programs, independent activities were undertaken in such areas as regulatory control of nondestructive testing, aging fleet evaluations, and measures to address the airworthiness of aging Canadian-manufactured airplanes.

Civil aviation↗