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NASA NTRS2007

A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a superparameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (2ICE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generatio11 regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

Tao, Wei-Kuo↗

NASA NTRS2006

A Coupled GCM-Cloud Resolving Modeling System, and A Regional Scale Model to Study Precipitation Processes

Tao, Wei-Kuo↗

NASA NTRS1989

The observation of possible reconnection events in the boundary changes of solar coronal holes

Coronal holes are large scale regions of magnetically open fields which are easily observed in solar soft X-ray images. The boundaries of coronal holes are separatrices between large scale regions of open and closed magnetic fields where one might expect to observe evidence of solar magnetic reconnection. Previous studies by Nolte and colleagues using Skylab X-ray images established that large scale (greater than or equal to 9 x 10(4) km) changes in coronal hole boundaries were due to coronal processes, i.e., magnetic reconnection, rather than to photospheric motions. Those studies were limited to time scales of about one day, and no conclusion could be drawn about the size and time scales of the reconnection process at hole boundaries. Sequences of appropriate Skylab X-ray images were used with a time resolution of about 90 min during times of the central meridian passages of the coronal hole labelled Coronal Hole 1 to search for hole boundary changes which can yield the spatial and temporal scales of coronal magnetic reconnection. It was found that 29 of 32 observed boundary changes could be associated with bright points. The appearance of the bright point may be the signature of reconnection between small scale and large scale magnetic fields. The observed boundary changes contributed to the quasi-rigid rotation of Coronal Hole 1.

Kahler, S. W.↗

NASA NTRS2021

Scaling photosynthetic function and CO2 dynamics from leaf to canopy level for maize – dataset combining diurnal and seasonal measurements of vegetation fluorescence, reflectance and vegetation indices with canopy gross ecosystem productivity

Recent advances in leaf fluorescence measurements and canopy proximal remote sensing currently enable the non-destructive collection of rich diurnal and seasonal time series, which are required for monitoring vegetation function at the temporal and spatial scales relevant to the natural dynamics of photosynthesis. Remote sensing assessments of vegetation function have traditionally used actively excited foliar chlorophyll fluorescence measurements, canopy optical reflectance data and vegetation indices (VIs), and only recently passive solar induced chlorophyll fluorescence (SIF) measurements. In general, reflectance data are more sensitive to the seasonal variations in canopy chlorophyll content and foliar biomass, while fluorescence observations more closely relate to the dynamic changes in plant photosynthetic function. With this dataset we link leaf level actively excited chlorophyll fluorescence, canopy proximal reflectance and SIF, with eddy covariance measurements of gross ecosystem productivity (GEP). The dataset was collected during the 2017 growing season on maize, using three automated systems (i.e., Monitoring Pulse-Amplitude-Modulation fluorimeter, Moni-PAM; Fluorescence Box, FloX; and from eddy covariance tower). The data were quality checked, filtered and collated to a common 30 minutes timestep. We derived vegetation indices related to canopy functioning (e.g., Photochemical Reflectance Index, PRI; Normalized Difference Vegetation Index, NDVI; Chlorophyll Red-edge, Clre) to investigate how SIF and VIs can be coupled for monitoring vegetation photosynthesis. The raw datasets and the filtered and collated data are provided to enable new processing and analyses.

Petya Campbell↗

NASA NTRS2001

Low Power Silicon Germanium Electronics for Microwave Radiometers

Space-based radiometric observations of key hydrological parameters (e.g., soil moisture) at the spatial and temporal scales required in the post-2002 era face significant technological challenges. These measurements are based on relatively low frequency thermal microwave emission (at 1.4 GHz for soil moisture and salinity, 10 GHz and up for precipitation, and 19 and 37 GHz for snow). The long wavelengths at these frequencies coupled with the high spatial and radiometric resolutions required by the various global hydrology communities necessitate the use of very large apertures (e.g., greater than 20 m at 1.4 GHz) and highly integrated stable RF electronics on orbit. Radio-interferometric techniques such as Synthetic Thinned Array Radiometry (STAR), using silicon germanium (SiGe) low power radio frequency integrated circuits (RFIC), is one of the most promising technologies to enable very large non-rotating apertures in space. STAR instruments are composed of arrays of small antenna/receiving elements that are arranged so that the collecting area is smaller than an equivalent real aperture system, allowing very high packing densities for launch. A 20 meter aperture at L-band, for example, will require greater than 1000 of these receiving elements. SiGe RFIC's reduce power consumption enough to make an array like this possible in the power-limited environment of space flight. An overview of the state-of-the-art will be given, and current work in the area of SiGe radiometer development for soil moisture remote sensing will be discussed.

Doiron, Terence A.↗

NASA NTRS2003

Hybrid Synthetic/Real Aperture Antenna for High Resolution Microwave Imaging

Observations of key hydrological parameters at the spatial and temporal scales required in the post-2002 era face significant technological challenges. These measurements are based on relatively low frequency thermal microwave emission (at 1.4 GHz for soil moisture and salinity, 10 GHz and up for precipitation, and 19 and 37 GHz for snow). The long wavelengths at these frequencies coupled with the high spatial and radiometric resolutions required by the various global hydrology missions necessitate the use of very large apertures. Two-dimensional Synthetic Thinned Array Radiometry (2-D STAR), though promising in the long term, has many technical challenges in the areas of power, and sensitivity for very large apertures (i.e. greater than 300 wavelengths). This paper will discuss an alternative approach to the pure 2-D STAR, which uses an offset parabolic cylinder reflector fed by multiple elements to form a 1-D STAR. In essence a single STAR element is composed of a feedhorn and parabolic cylinder reflector. The elements are sparsely arrayed and thus can share a single reflector. This antenna would have no moving parts once deployed, have much higher sensitivity than a Y-shaped 2-D STAR of equivalent size, many fewer receivers than that 2-D STAR, and the reflector could be made of a thin film and lightweight deployment system for high packing density. The instrument using this approach would be a cross track push broom imager. An overview of the design parameters, potential deployment mechanisms and applications will be presented.

Doiron, Terence A.↗

NASA NTRS1990

The observation of possible reconnection events in the boundary changes of solar coronal holes

Coronal holes are large scale regions of magnetically open fields which are easily observed in solar soft X-ray images. The boundaries of coronal holes are separatrices between large-scale regions of open and closed magnetic fields where one might expect to observe evidence of solar magnetic reconnection. Previous studies by Nolte and colleagues using Skylab X-ray images established that large-scale (more than 90,000 km) changes in coronal hole boundaries were due to coronal processes, i.e., magnetic reconnection, rather than to photospheric motions. Those studies were limited to time scales of about one day, and no conclusion could be drawn about the size and time scales of the reconnection process at hole boundaries. Sequences of approximate Skylab X-ray images with a time resolution of about 90 min are here used during times of the central meridian passages of the coronal hole labelled 'Coronal Hole 1' to search for hole-boundary changes which can yield the spatial and temporal scales of coronal magnetic reconnection. It is found that 29 of 32 observed boundary changes could be associated with bright points. The appearance of the bright point may be the signature of reconnection between small-scale and large-scale magnetic fields. The observed boundary changes contributed to the quasi-rigid rotation of Coronal Hole 1.

Kahler, S. W.↗

NASA NTRS2024

Investigating the Spatial and Temporal Limitations for Remote Sensing of Wildfire Smoke Using Satellite and Airborne Imagers During FIREX_AQ

Starting from point sources, wildfire smoke is important in the global aerosol system. The ability to characterize smoke near-source is key to modeling smoke dispersion and predicting air quality. With hemispheric views and 10-min refresh, imagers in Geostationary (GEO) orbit have advantages monitoring smoke over once-per-day sensors in low-earth orbit (LEO). However, both can be inadequate in capturing the characteristics of smoke plumes close to their sources due to too-coarse spatial resolution (both detector and product resolution), too-sparse temporal resolution (from LEO sensors), and too-conservative masking. In addition to satellite observations, the Fire Influence on Regional to Global Environments and Air Quality experiment offered sub-orbital enhanced-MODIS Airborne Simulator (eMAS) imagery at 50 m pixel resolution—including multiple eMAS flight tracks over individual fires in short time periods. It provided opportunity to explore smoke plume characterization at various spatial and temporal scales and quantify the limitations of space sensors for describing smoke magnitude near source as well as its temporal evolution. Here we applied modified aerosol algorithm to different imagers, relaxing its masking to estimate smoke's aerosol optical depth (AOD) as close as possible to its source. We found that GEO sensors with nominal 1 km spatial resolution can match the much finer resolution eMAS retrieved mean plume AOD, as long as the retrieval spatial resolution is finer than the width of the plumes. However, the plume's maximum AOD may be drastically underestimated by satellite products.

remote sensing↗

NASA NTRSDate not supplied

Using Open Innovation in Reducing Risk to Crews

In the exploration of destinations outside of Earth's neighborhood, specifically Mars, scientific and engineering inquiries have occurred by two means; observations from satellites and observations by landed spacecraft. Satellite observations (Mariner, MRO, Mars Odyssey, provide global-scale spatial and temporal data while landed spacecraft (Viking, Mars Pathfinder, Spirit, Opportunity, Phoenix Mars Lander) investigate highly localized areas of the surface of the planet. In preparation for human exploration, extensive knowledge of the surface and atmospheric environments should be known before the first human leaves Earth. The primary goal of performing reconnaissance on Mars on a sub-global scale is to know as much as possible about the environment to which crews will be subjected. At the current rate of launching and landing probes to Mars, it will take a very long time to understand the surface and atmospheric conditions associated with the regions where prospective crews may land. Meanwhile electronics and electrical systems are rapidly getting smaller. One can argue that to acquire the knowledge of the region, one must take hundreds, maybe thousands of measurements simultaneously. One means to perform such a task is to deploy a swarm of sensors. Such a swarm would perform an in-situ assessment of the region. Imagine a close flyby mission to Mars for example, where mini- to micro-sensors are deposited into the atmosphere over half an orbit or more. The sensors, captured by the atmospheric drag and Martian gravity slowly descend buffeted about by Martian winds and weather until they settle on the surface a great time later (think of how long dust takes to settle). As they descend they communicate a vast array of data; temperature, chemistry, pressure, radiation dose, electric or magnetic properties from a region of the planet and an individual sensor need not measure the same quantity as its neighbors. Initially, they could move at the whim of the environment but later versions could have locomotion or propulsion mechanisms. Humans wouldn't need to decide where the sensors go, the sensors do that for themselves. This is a key strength of a sensor swarm. The intelligence relies on the group not on a decision maker on earth. Real time sensor inputs direct what the swarm considers most interesting to investigate resulting in emergent behavior. We issued a $20,000 challenge to the global innovators to provide solutions as to how such a swarm could be initialized and by what protocols and methodologies by which they operate. Over 400 innovators from 49 countries took a look at the problem, with three receiving partial awards for solutions.

Mel Ferebee↗

NASA NTRSDate not supplied

Moving With Parasites: Relationships Between Animal Movement and Infectious Disease Across Systems and Scales

Animal movement patterns are important for ecological processes such as population dynamics and infectious disease transmission. Because animals move in response to environmental cues like temperature and precipitation, changes to the environment – whether they are seasonal, interannual, or long-term – can change these processes, leading to changes in population sizes or infectious disease prevalence across space and time. My work uses a combination of simulation modeling and data analysis at multiple spatial and temporal scales to understand the environment-movement-disease connection in diverse animal taxa and environments. In this seminar, I will highlight the diverse ways that the environment can influence infectious disease dynamics via changes to animal movement patterns, including through a global study of migration in ungulate populations, a study of American White Ibis adapting to urban environments in South Florida, and examples of avian influenza prevalence in wild waterfowl. Together, these examples highlight that understanding environment-movement interactions can help predict how infectious disease dynamics might change in the future, as changes to climate, land use, and habitats alter animal movement patterns.

Animal movement↗

NASA NTRS2013

A Stochastic Fractional Dynamics Model of Space-time Variability of Rain

Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment.

TRMM↗

NASA NTRSDate not supplied

Maintaining the Continuity of the Global Climate Data Record of Lightning from Space

Lightning is a natural hazard, an indicator of changes in convective storm behavior across multiple spatial and temporal scales, and a major influence on climate-affecting chemicals such as ozone and methane. Lightning also has substantial impacts on the near-space environment. As such, the World Meteorological Organization (WMO) has designated lightning as an Essential Climate Variable (ECV); that is, a measurement that is really important for understanding Earth’s climate. Spaceborne lightning observations are the gold standard for measuring global lightning, as the detection efficiency is more spatially uniform compared to ground-based lightning measurements. In addition, spaceborne is the only practical method for measuring total lightning (i.e., both intracloud and cloud-to-ground) at the global scale, as ground-based networks have limited ability to detect intracloud lightning at long distances (e.g., over oceans, far from land-based sensors). Since 1995, with only a two-year gap (2015-2017), lightning has been observed globally using a combination of Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) instruments. However, the year 2023 is the planned end for the International Space Station (ISS) LIS mission, and there is no designated low-Earth orbit (LEO) successor yet identified. Since 2017, geostationary (GEO) observations of lightning have become increasingly available. These include the U.S. Geostationary Lightning Mappers (GLMs), China’s Lightning Mapping Imager (LMI), and Europe’s Lightning Imager (LI). While GEO provides continuous, quasi-hemispheric coverage of lightning and thunderstorms, there are current gaps preventing global coverage, particularly in portions of Asia and the western Pacific, as well as high-latitude regions. Moreover, integration of the GEO constellation into a Climate Data Record (CDR) of lightning is a major challenge only recently begun to be addressed by the WMO. Furthermore, recent work has demonstrated some deficiencies in the global record of lightning from space. For example, small lightning flashes are very common in severe weather, but are difficult to observe using the present set of spaceborne lightning imagers. Moreover, some types of lightning are best observed using frequencies other than the commonly used near-infrared (777-nm), including ultraviolet and the radio spectrum. Finally, it is not possible to assess the vertical distribution of lightning globally, even though this measurement is highly relevant to thunderstorm behavior as well as lightning’s effects on greenhouse gases and the near-space environment. This presentation will provide a current assessment of lightning measurements from space, will identify significant current and future gaps in these observations, and will evaluate potential solutions for improving the overall CDR of global lightning.

Timothy Lang↗

NASA NTRSDate not supplied

Bridging the Last Mile with Open-Source Advancements: Empowering Communities through Fusion of Aerosol Optical Depth (AOD) Products from Multi-Satellite Sensors

Aerosol Optical Depth (AOD) is a crucial parameter for understanding atmospheric aerosol distribution and their impact on climate and air quality. With the growing number of Earth observation satellites, there is an abundance of AOD products derived from various sensors onboard both geostationary and low-orbit satellites. The availability of multiple datasets provides an opportunity to harness the strengths of each sensor and create comprehensive and accurate AOD datasets for climate and air quality studies at different temporal and spatial scales. Our NASA aerosol MEaSURES project has made significant strides in recent years by undertaking the ambitious task of developing an open-source package tailored for fusing AOD products from different sources. The package is based on OOP (Object-Oriented Programming) design and is implemented in Python modules. Generic interfaces enable easy inclusion of large and heterogeneous data. The package may be utilized to produce harmonized AOD datasets with enhanced spatial and temporal coverage. The latest version of the package is able to process and integrate the dark-target AOD data from six different sensors: AHI Himawari-8, ABI GOES-West, ABI GOES-East, MODIS AQUA, MODIS TERRA, and VIIRS SNPP. Rigorous validation and intercomparison studies have been performed to assess the accuracy and reliability of the fused AOD product against ground-based measurements and reference datasets. The open-source nature of the developed package ensures transparency, reproducibility, and community engagement. The research community and stakeholders can access, contribute to, and further improve the fusion methodology, making it adaptable to other studies, or expanding it to include new satellite data as they become available. In this poster presentation, we will introduce the accomplishments and challenges faced during the development of the open-source package for AOD data fusion, and demonstrate the advantages of combining AOD products from the six aforementioned satellite sensors. The presentation aims to foster discussions, collaborations, and future directions in integrating Earth observation and remote sensing data, which may contribute to a better understanding of atmospheric aerosols and their impacts on our environment.

Zhaohui Zhang↗

NASA NTRS1984

Mesoscale budgets of heat and moisture in a convective system over the central United States

Mesoscale heat and moisture budget calculations from the April 10-11 AVE-SESAME central U.S. region are calculated in order to diagnose the effect of midlatitude organized convection on its environment. When averaged over an area greater than the observational scale, the noise levels of 5 C/day for the heat budget and 2 g/kg per day for the moisture budget are considerably reduced. The credibility of such area-averaged budget results is indicated by the general agreement obtained between the observed rainfall rate and the vertically integrated heat sources and moisture sinks. The vertical convective heating that is diagnosed from this organized midlatitude convection differs significantly from tropical structures diagnosed on much larger temporal and spatial scales. A time lag of several hours between the moisture convergence and rainfall rate is noted.

Kuo, Y.-H.↗

NASA NTRS2022

Evaluation of Retrieving Chlorophyll a Concentration and Colored Dissolved Organic Matter Absorption from Satellite Ocean Color Remote Sensing in the Coastal Waters of Hokkaido, Japan

Coastal ecosystems are important in biogeochemical cycles, because they provide many pathways for chemical elements and compounds to flow between the physical environment and living organisms. The spatial and temporal scales of the biotic and abiotic interactions establish the inherent dynamics of the coastal zone and the requirement for high-resolution investigations. Using match-up data collected in Hokkaido coastal waters, the study herein evaluated the performance of deriving chlorophyll (Chl) a concentration and colored dissolved organic matter (CDOM) absorption (a(sub CDOM)) as a function of wavelength (λ) from satellite observations. The Japanese Aerospace Exploration Agency (JAXA) Second generation GLobal Imager (SGLI), which has 250 m spatial resolution, was compared with other satellite ocean color (OC) sensors. Our results show that the standard SGLI OC4 algorithm with the 530 nm band provided the best performance for Chl a retrievals, and the end-member analysis (EMA) technique improved the estimation of a(sub CDOM)(λ) . Overall differences between in situ radiometric data and satellite retrievals suggest that additional challenges remain, especially in the ultraviolet and blue spectral domains which are useful for studying CDOM and harmful algae blooms in coastal waters. To fulfill applications wherein high-quality remote sensing data are required, the improvement of the atmospheric correction is a likely research area where additional accomplishment will be beneficial for satellite observations of optically complex coastal waters.

SGLI/GCOM-C↗

NASA NTRS2002

Subtropical Gyre Variability Observed by Ocean Color Satellites

The subtropical gyres of the world are extensive, coherent regions that occupy about 40% of the surface of the earth. Once thought to be homogeneous and static habitats, there is increasing evidence that mid-latitude gyres exhibit substantial physical and biological variability on a variety of time scales. While biological productivity within these oligotrophic regions may be relatively small, their immense size makes their total contribution significant. Global distributions of dynamic height derived from satellite altimeter data, and chlorophyll concentration derived from satellite ocean color data, show that the dynamic center of the gyres, the region of maximum dynamic height where the thermocline is deepest, does not coincide with the region of minimum chlorophyll concentration. The physical and biological processes by which this distribution of ocean properties is maintained, and the spatial and temporal scales of variability associated with these processes, are analyzed using global surface chlorophyll-a concentrations, sea surface height, sea surface temperature and surface winds from operational satellite and meteorological sources, and hydrographic data from climatologies and individual surveys. Seasonal and interannual variability in the areal extent of the subtropical gyres are examined using 8 months (November 1996 - June 1997) of OCTS and nearly 5 years (September 1997 - June 02) of SeaWiFS ocean color data and are interpreted in the context of climate variability and measured changes in other ocean properties (i.e., wind forcing, surface currents, Ekman pumping, and vertical mixing). The North Pacific and North Atlantic gyres are observed to be shrinking over this period, while the South Pacific, South Atlantic, and South Indian Ocean gyres appear to be expanding.

McClain, Charles R.↗

NASA NTRS2023

CME Propagation Through the Heliosphere: Status and Future of Observations and Model Development

The ISWAT (International Space Weather Action Teams) heliosphere clusters H1 and H2 have a focus on interplanetary space and its characteristics, especially on the large-scale co-rotating and transient structures impacting Earth. Solar wind stream interaction regions, generated by the interaction between high-speed solar wind originating in large-scale open coronal magnetic fields and slower solar wind from closed magnetic fields, are regions of compressed plasma and magnetic field followed by high-speed streams that recur at the ~27 day solar rotation period. Short-term reconfigurations of the lower coronal magnetic field generate flare emissions and provide the energy to accelerate enormous amounts of magnetised plasma and particles in the form of coronal mass ejections into interplanetary space. The dynamic interplay between these phenomena changes the configuration of interplanetary space on various temporal and spatial scales which in turn influences the propagation of individual structures. While considerable efforts have been made to model the solar wind, we outline the limitations arising from the rather large uncertainties in parameters inferred from observations that make reliable predictions of the structures impacting Earth difficult. Moreover, the increased complexity of interplanetary space as solar activity rises in cycle 25 is likely to pose a challenge to these models. Combining observational and modeling expertise will extend our knowledge of the relationship between these different phenomena and the underlying physical processes, leading to improved models and scientific understanding and more-reliable space-weather forecasting. The current paper summarizes the efforts and progress achieved in recent years, identifies open questions, and gives an outlook for the next 5–10 years. It acts as basis for updating the existing COSPAR roadmap by Schrijver et al. (2015), as well as providing a useful and practical guide for peer-users and the next generation of space weather scientists.

Space weather↗

NASA NTRSDate not supplied

Development of Computational Materials Workflows for Additively Manufactured Metallic Materials to Enable Accelerated Prediction of Fatigue Performance

The maturation of computational materials approaches for fatigue performance prediction in a qualification and certification process is stifled by the ability to validate complex, microstructure-based simulations. Such a validation strategy bears immediate challenges including generating accurate virtual microstructures, efficiently solving physics-based mechanical simulations over relevant spatial and temporal scales, and acquiring high-fidelity calibration and validation data at the appropriate length scale. This presentation will overview these common challenges and present a case study to demonstrate a computational materials workflow for additively manufactured metallic materials. In this study, process-specific defects are characterized using segmented X-Ray micro-computed tomography measurements and overlaid on virtual microstructures. Accelerated crystal plasticity-based fatigue simulations are performed to demonstrate cyclic evolution and localization of mechanical fields in the vicinity of defects in response to their precise spatial configuration. An example of how this computational materials workflow may support next-generation qualification is discussed.

computational materials↗