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NASA NTRS2006

Dynamic Fracture Initiation Toughness at Elevated Temperatures With Application to the New Generation of Titanium Aluminide Alloys

Recently, a new generation of titanium aluminide alloy, named Gamma-Met PX, has been developed with better rolling and post-rolling characteristics. I'revious work on this alloy has shown the material to have higher strengths at room and elevated temperatures when compared with other gamma titanium aluminides. In particular, this new alloy has shown increased ductility at elevated temperatures under both quasi-static and high strain rate uniaxial compressive loading. However, its high strain rate tensile ductility at room and elevated temperatures is limited to approx. 1%. In the present chapter, results of a study to investigate the effects of loading rate and test temperature on the dynamic fracture initiation toughness in Gamma-Met PX are presented. Modified split Hopkinson pressure bar was used along with high-speed photography to determine the crack initiation time. Three-point bend dynamic fracture experiments were conducted at impact speeds of approx. 1 m/s and tests temperatures of up-to 1200 C. The results show that thc dynamic fracture initiation toughness decreases with increasing test temperatures beyond 600 C. Furthermore, thc effect of long time high temperature air exposure on the fracture toughness was investigated. The dynamic fracture initiation toughness was found to decrease with increasing exposure time. The reasons behind this drop are analyzed and discussed.

Shazly, Mostafa↗

NASA NTRS2010

Hybrid Black-Hole Binary Initial Data

"Traditional black-hole binary puncture initial data is conformally flat. This unphysical assumption is coupled with a lack of radiation signature from the binary's past life. As a result, waveforms extracted from evolutions of this data display an abrupt jump. In Kelly et al. [Class. Quantum Grav. 27:114005 (2010)], a new binary black-hole initial data with radiation contents derived in the post-Newtonian (PN) calculations was adapted to puncture evolutions in numerical relativity. This data satisfies the constraint equations to the 2.5PN order, and contains a transverse-traceless "wavy" metric contribution, violating the standard assumption of conformal flatness. Although the evolution contained less spurious radiation, there were undesired features; the unphysical horizon mass loss and the large initial orbital eccentricity. Introducing a hybrid approach to the initial data evaluation, we significantly reduce these undesired features."

Mundim, Bruno C.↗

NASA NTRS2011

Analysis of Summertime Convective Initiation in Central Alabama Using the Land Information System

During the summer months in the southeastern United States, convective initiation presents a frequent challenge to operational forecasters. Thunderstorm development has traditionally been referred to as random due to their disorganized, sporadic appearance and lack of atmospheric forcing. Horizontal variations in land surface characteristics such as soil moisture, soil type, land and vegetation cover could possibly be a focus mechanism for afternoon convection during the summer months. The NASA Land Information System (LIS) provides a stand-alone land surface modeling framework that incorporates these varying soil and vegetation properties, antecedent precipitation, and atmospheric forcing to represent the soil state at high resolution. The use of LIS as a diagnostic tool may help forecasters to identify boundaries in land surface characteristics that could correlate to favored regions of convection initiation. The NASA Shortterm Prediction Research and Transition (SPoRT) team has been collaborating with the National Weather Service Office in Birmingham, AL to help incorporate LIS products into their operational forecasting methods. This paper highlights selected convective case dates from summer 2009 when synoptic forcing was weak, and identifies any boundaries in land surface characteristics that may have contributed to convective initiation. The LIS output depicts the effects of increased sensible heat flux from urban areas on the development of convection, as well as convection along gradients in land surface characteristics and surface sensible and latent heat fluxes. These features may promote mesoscale circulations and/or feedback processes that can either enhance or inhibit convection. With this output previously unavailable to operational forecasters, LIS provides a new tool to forecasters in order to help eliminate the randomness of summertime convective initiation.

James, Robert S.↗

NASA NTRS2011

Improving Numerical Weather Predictions of Summertime Precipitation Over the Southeastern U.S. Through a High-Resolution Initialization of the Surface State

It is hypothesized that high-resolution, accurate representations of surface properties such as soil moisture and sea surface temperature are necessary to improve simulations of summertime pulse-type convective precipitation in high resolution models. This paper presents model verification results of a case study period from June-August 2008 over the Southeastern U.S. using the Weather Research and Forecasting numerical weather prediction model. Experimental simulations initialized with high-resolution land surface fields from the NASA Land Information System (LIS) and sea surface temperature (SST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared to a set of control simulations initialized with interpolated fields from the National Centers for Environmental Prediction 12-km North American Mesoscale model. The LIS land surface and MODIS SSTs provide a more detailed surface initialization at a resolution comparable to the 4-km model grid spacing. Soil moisture from the LIS spin-up run is shown to respond better to the extreme rainfall of Tropical Storm Fay in August 2008 over the Florida peninsula. The LIS has slightly lower errors and higher anomaly correlations in the top soil layer, but exhibits a stronger dry bias in the root zone. The model sensitivity to the alternative surface initial conditions is examined for a sample case, showing that the LIS/MODIS data substantially impact surface and boundary layer properties.

Case, Jonathan L.↗

NASA NTRS2011

Lightning Initiation Forecasting: An Operational Dual-Polarimetric Radar Technique

The objective of this NASA MSFC and NOAA CSTAR funded study is to develop and test operational forecast algorithms for the prediction of lightning initiation utilizing the C-band dual-polarimetric radar, UAHuntsville's Advanced Radar for Meteorological and Operational Research (ARMOR). Although there is a rich research history of radar signatures associated with lightning initiation, few studies have utilized dual-polarimetric radar signatures (e.g., Z(sub dr) columns) and capabilities (e.g., fuzzy-logic particle identification [PID] of precipitation ice) in an operational algorithm for first flash forecasting. The specific goal of this study is to develop and test polarimetric techniques that enhance the performance of current operational radar reflectivity based first flash algorithms. Improving lightning watch and warning performance will positively impact personnel safety in both work and leisure environments. Advanced warnings can provide space shuttle launch managers time to respond appropriately to secure equipment and personnel, while they can also provide appropriate warnings for spectators and players of leisure sporting events to seek safe shelter. Through the analysis of eight case dates, consisting of 35 pulse-type thunderstorms and 20 non-thunderstorm case studies, lightning initiation forecast techniques were developed and tested. The hypothesis is that the additional dual-polarimetric information could potentially reduce false alarms while maintaining high probability of detection and increasing lead-time for the prediction of the first lightning flash relative to reflectivity-only based techniques. To test the hypothesis, various physically-based techniques using polarimetric variables and/or PID categories, which are strongly correlated to initial storm electrification (e.g., large precipitation ice production via drop freezing), were benchmarked against the operational reflectivity-only based approaches to find the best compromise between forecast skill and lead-time. Forecast skill is determined by statistical analysis of probability of detection (POD), false alarm ratio (FAR), Operational Utility Index (OUI), and critical success index (CSI).

Woodard, Crystal J.↗

NASA NTRS2007

Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

This report describes the work done by the Applied Meteorology Unit (AMU) in assessing the success of different model configurations in predicting warm season convection over East-Central Florida. The Weather Research and Forecasting Environmental Modeling System (WRF EMS) software allows users to choose among two dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). There are also data assimilation analysis packages available for the initialization of the WRF model - the Local Analysis and Prediction System (LAPS) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS). Besides model core and initialization options, the WRF model can be run with one- or two-way nesting. Having a series of initialization options and WRF cores, as well as many options within each core, creates challenges for local forecasters, such as determining which configuration options are best to address specific forecast concerns. This project assessed three different model intializations available to determine which configuration best predicts warm season convective initiation in East-Central Florida. The project also examined the use of one- and two-way nesting in predicting warm season convection.

Watson, Leela R.↗

NASA NTRS2012

The Second Phase of the Global Land Atmosphere Coupling Experiment (GLACE-2): Impact of Land Initialization on Subseasonal Forecasts

The recently-completed second phase of the Global Land-Atmosphere Coupling Experiment (GLACE-2) focused on quantifying, for boreal summer, the subseasonal (out to two months) forecast skill for precipitation and air temperature that can be derived from the realistic initialization of land surface states, notably soil moisture. An overview of the multi-institutional numerical experiment is described, along with a determination and characterization of multi-model "consensus" skill. The models show modest but significant land-derived skill in predicting air temperatures out to two months, especially where the rain gauge network is dense. Given that precipitation is the chief driver of soil moisture, and thereby assuming that rain gauge density is a reasonable proxy for the adequacy of the observational network contributing to soil moisture initialization, this result indeed highlights the potential contribution of enhanced observations to prediction. Land-derived precipitation forecast skill is much weaker than that for air temperature. The skill for predicting air temperature, and to some extent precipitation, increases with the magnitude of the initial soil moisture anomaly. GLACE-2 results are examined further to provide insight into the asymmetric impacts of wet and dry soil moisture initialization on skill.

Koster, Randal↗

NASA NTRS2016

Transitioning Enhanced Land Surface Initialization and Model Verification Capabilities to the Kenya Meteorological Department (KMD)

Flooding, severe weather, and drought are key forecasting challenges for the Kenya Meteorological Department (KMD), based in Nairobi, Kenya. Atmospheric processes leading to convection, excessive precipitation and/or prolonged drought can be strongly influenced by land cover, vegetation, and soil moisture content, especially during anomalous conditions and dry/wet seasonal transitions. It is thus important to represent accurately land surface state variables (green vegetation fraction, soil moisture, and soil temperature) in Numerical Weather Prediction (NWP) models. The NASA SERVIR and the Short-term Prediction Research and Transition (SPoRT) programs in Huntsville, AL have established a working partnership with KMD to enhance its regional modeling capabilities. SPoRT and SERVIR are providing experimental land surface initialization datasets and model verification capabilities for capacity building at KMD. To support its forecasting operations, KMD is running experimental configurations of the Weather Research and Forecasting (WRF; Skamarock et al. 2008) model on a 12-km/4-km nested regional domain over eastern Africa, incorporating the land surface datasets provided by NASA SPoRT and SERVIR. SPoRT, SERVIR, and KMD participated in two training sessions in March 2014 and June 2015 to foster the collaboration and use of unique land surface datasets and model verification capabilities. Enhanced regional modeling capabilities have the potential to improve guidance in support of daily operations and high-impact weather and climate outlooks over Eastern Africa. For enhanced land-surface initialization, the NASA Land Information System (LIS) is run over Eastern Africa at ~3-km resolution, providing real-time land surface initialization data in place of interpolated global model soil moisture and temperature data available at coarser resolutions. Additionally, real-time green vegetation fraction (GVF) composites from the Suomi-NPP VIIRS instrument is being incorporated into the KMD-WRF runs, using the product generated by NOAA/NESDIS. Model verification capabilities are also being transitioned to KMD using NCAR's Model *Corresponding author address: Jonathan Case, ENSCO, Inc., 320 Sparkman Dr., Room 3008, Huntsville, AL, 35805. Email: Jonathan.Case-1@nasa.gov Evaluation Tools (MET; Brown et al. 2009) software in conjunction with a SPoRT-developed scripting package, in order to quantify and compare errors in simulated temperature, moisture and precipitation in the experimental WRF model simulations. This extended abstract and accompanying presentation summarizes the efforts and training done to date to support this unique regional modeling initiative at KMD. To honor the memory of Dr. Peter J. Lamb and his extensive efforts in bolstering weather and climate science and capacity-building in Africa, we offer this contribution to the special Peter J. Lamb symposium. The remainder of this extended abstract is organized as follows. The collaborating international organizations involved in the project are presented in Section 2. Background information on the unique land surface input datasets is presented in Section 3. The hands-on training sessions from March 2014 and June 2015 are described in Section 4. Sample experimental WRF output and verification from the June 2015 training are given in Section 5. A summary is given in Section 6, followed by Acknowledgements and References.

land surface modeling↗

NASA NTRS2016

Stirling to Flight Initiative

NASA has a consistent need for radioisotope power systems (RPS) to enable robotic scientific missions for planetary exploration that has been present for over four decades and will continue into the foreseeable future, as documented in the most recent Planetary Science Decadal Study Report. As RPS have evolved throughout the years, there has also grown a desire for more efficient power systems, allowing NASA to serve as good stewards of the limited plutonium-238 (238Pu), while also supporting the ever-present need to minimize mass and potential impacts to the desired science measurements. In fact, the recent Nuclear Power Assessment Study (NPAS) released in April 2015 resulted in several key conclusion regarding RPS, including affirmation that RPS will be necessary well into the 2030s (at least) and that 238Pu is indeed a precious resource requiring efficient utilization and preservation. Stirling Radioisotope Generators (SRGs) combine a Stirling cycle engine powered by a radioisotope heater unit into a single generator system. Stirling engine technology has been under development at NASA Glenn Research Center (GRC) in partnership with the Department of Energy (DOE) since the 1970's. The most recent design, the 238Pu-fueled Advanced Stirling Radioisotope Generator (ASRG), was offered as part of the NASA Discovery 2010 Announcement of Opportunity (AO). The Step-2 selections for this AO included two ASRG-enabled concepts, the Titan Mare Explorer (TiME) and the Comet Hopper (CHopper), although the only non-nuclear concept, InSight, was ultimately chosen. The DOE's ASRG contract was terminated in 2013. Given that SRGs utilize significantly less 238Pu than traditional Radioisotope Thermoelectric Generators (RTGs) - approximately one quarter of the nuclear fuel, to produce similar electrical power output - they provide a technology worthy of consideration for meeting the aforementioned NASA objectives. NASA's RPS Program Office has recently investigated a new Stirling to Flight (S2F) initiative with the objective of developing a 100-500 We Stirling generator system. Additionally, a different approach is being devised for this initiative to avoid pitfalls of the past, and apply lessons learned from the recent ASRG experience. Two key aspects of this initiative are a Stirling System Technology Maturation Effort, and a Surrogate Mission Team (SMT) intended to provide clear mission pull and requirements context. The S2F project seeks to lead directly into a DOE flight system development of a new SRG. This paper will detail the proposed S2F initiative, and provide specifics on the key efforts designed to pave a forward path for bringing Stirling technology to flight.

Robotics↗

NASA NTRS2017

Increasing Small Satellite Reliability- A Public-Private Initiative

At present, CubeSat components and buses are generally not appropriate for missions where significant risk of failure, or the inability to quantify risk or confidence, is acceptable. However, in the future we anticipate that CubeSats will be used for missions requiring reliability of 1-3 years for Earth-observing missions and even longer for Planetary, Heliophysics, and Astrophysics missions. Their growing potential utility is driving an interagency effort to improve and quantify CubeSat reliability, and more generally, small satellite mission risk. The Small Satellite Reliability Initiative (SSRI)—an ongoing activity with broad collaborative participation from civil, DoD, and commercial space systems providers and stakeholders—targets this challenge. The Initiative seeks to define implementable and broadly-accepted approaches to achieve reliability and acceptable risk postures associated with several SmallSat mission risk classes—from “do no harm” missions, to those associated with missions whose failure would result in loss or delay of key national objectives. These approaches will maintain, to the extent practical, cost efficiencies associated with small satellite missions and consider constraints associated with supply chain elements, as appropriate. The SSRI addresses this challenge from two architectural levels—the mission- or system-level, and the component- or subsystem-level. The mission- or system-level scope targets assessment approaches that are efficient and effective, with mitigation strategies that facilitate resiliency to mission or system anomalies while the component- or subsystem-level scope addresses the challenge at lower architectural levels. The initiative does not limit strategies and approaches to proven and traditional methodologies, but is focused on fomenting thought on novel and innovative solutions. This paper discusses the genesis of and drivers for this initiative, how the public-private collaboration is being executed, findings and recommendations derived to date, and next steps towards broadening small satellite mission potential.

SmallSat↗

NASA NTRS2012

A Robust Initialization Scheme for a Lateral Trajectory Optimization Problem with Time of Arrival Windows

We present a robust initialization scheme that estimates parameter values for the numerical solution of a two-point boundary value problem. The two-point boundary value problem formulation stems from the optimization of a cost functional subject to the dynamics of a simplified lateral aircraft model and other constraints. Leveraging regular perturbation methods, initial parameter estimates are analytically determined and used to initialize a gradient descent optimization routine which is shown to rapidly converge over a range of initial aircraft positions and heading angles. Additionally, the velocity of the aircraft is optimized to ensure the trajectory of the aircraft terminates within a desired region in both time and space.

lateral trajectory optimization↗

NASA NTRS2018

An Engineering Approach to Analyze Damage Initiation Modes in Tapered Composite Structures

In this work an engineering approach is demonstrated for analyzing damage initiation modes in tapered composite structures. The analysis methodology includes simulation of the non-linear static response of tapered composite structures under static tension loads to predict the location of interfacial delamination initiation. Furthermore, the developed methodology provides a strength-based criterion to assess whether damage initiation will occur in the inter-laminar delamination or intra-laminar matrix cracking mode. Based on the results of the analysis, a tapered composite structure is fabricated and tested under displacement-controlled quasi-static tension loading. The damage initiation location captured experimentally is compared with the analysis towards achieving preliminary qualitative validation. The linear stiffness of the tapered composite structure is predicted within 15% of the experimental average thereby achieving preliminary quantitative validation.

Rao, Prabhakar M.↗

NASA NTRSDate not supplied

An Engineering Approach to Analyze Damage Initiation Modes in Tapered Composite Structures

Prabhakar M Rao↗

NASA NTRS2020

Using a Simple Water Balance Framework to Quantify the Impact of Soil Moisture Initialization on Subseasonal Evapotranspiration and Air Temperature Forecasts

Past studies have shown that accurate soil moisture initialization can contribute significant skill to near-surface air temperature (T2M) forecasts at subseasonal leads. The mechanisms by which soil moisture contributes such skill are examined here with a simple water balance-based model that captures the essence of soil moisture behavior in a state-of-the-art subseasonal-to-seasonal (S2S) forecasting system. The simple model successfully transforms initial soil moisture contents into average “forecasted” ET values at 16-30 day lead that agree well, during summer, with the values forecasted by the full NASA GEOS S2S system, indicating that soil moisture initialization dominates over forecasted meteorology in determining ET fluxes at subseasonal leads. When the simple model’s ET anomalies are interpreted in terms of T2M anomalies, a similar conclusion is reached for T2M: soil moisture initialization explains much (about 50% in the eastern half of the continental US) of the T2M anomalies produced by the full GEOS S2S system at 16-30 day lead, and the T2M forecasts produced by the simple model capture about half of the skill attained by the full system. The simple model’s framework is particularly conducive to an analysis of uncertainty in forecasts. Drier soils are generally found to induce larger uncertainty in ET (and thus T2M) forecasts, a result linked to the functional form relating ET to soil moisture in the simple model and verified by an analysis of the ensemble spreads within the forecasts produced by the full GEOS S2S system

Randal D Koster↗

NASA NTRS2021

Asymmetry in Subseasonal Surface Air Temperature Forecast Error with Respect to Soil Moisture Initialization

Soil moisture (W) helps control evapotranspiration (ET), and ET variations can in turn have a distinct impact on 2-m air temperature (T2M), given that increases in evaporative cooling encourage reduced temperatures. Soil moisture is accordingly linked to T2M, and realistic soil moisture initialization has, in previous studies, been shown to improve the skill of subseasonal T2M forecasts. The relationship between soil moisture and evapotranspiration, however, is distinctly nonlinear, with ET tending to increase with soil moisture in drier conditions and to be insensitive to soil moisture variations in wetter conditions. Here, through an extensive analysis of subseasonal forecasts produced with a state-of-the-art seasonal forecast system, this nonlinearity is shown to imprint itself on T2M forecast error in the conterminous United States in two unique ways: (i) the T2M forecast bias (relative to independent observations) induced by a negative precipitation bias tends to be larger for dry initializations, and (ii) on average, the unbiased root-mean-square error (ubRMSE) tends to be larger for dry initializations. Such findings can aid in the identification of forecasts of opportunity; taken a step further, they suggest a pathway for improving bias correction and uncertainty estimation in subseasonal T2M forecasts by conditioning each on initial soil moisture state.

Air Temperature↗

NASA NTRSDate not supplied

T2M Forecasts at Subseasonal Leads: Do Different Soil Moisture Initial States Have Different Impacts?

2-meter Temperature↗

NASA NTRS2021

The Climate Response to Emissions Reductions due to COVID-19: Initial Results from CovidMIP

Many nations responded to the COVID-19 pandemic by restricting travel and other activities during 2020, resulting in temporarily reduced emissions of CO2, other greenhouse gases and ozone and aerosol precursors. We present the initial results from a coordinated Intercomparison, CovidMIP, of Earth system model simulations which assess the impact on climate of these emissions reductions. Twelve models performed multiple initial-condition ensembles to produce over 300 simulations spanning both initial condition and model structural uncertainty. We find model consensus on reduced aerosol amounts (particularly over southern and eastern Asia) and associated increases in surface shortwave radiation levels. However, any impact on near-surface temperature or rainfall during 2020-2024 is extremely small and is not detectable in this initial analysis. Regional analyses on a finer scale, and closer attention to extremes (especially linked to changes in atmospheric composition and air quality) are required to test the impact of COVID- 19-related emission reductions on near-term climate.

Chris D. Jones↗

NASA NTRS2020

Analyzing the Impact of CryoSat-2 Ice Thickness Initialization on Seasonal Arctic Sea Ice Prediction

Twin 5-month seasonal forecast experiments are performed to predict the September 2018 minimum ice extent using the fully coupled Navy Earth System Prediction Capability (ESPC). In the control run, ensemble forecasts are initialized from the operational US Navy Global Ocean Forecasting System (GOFS) 3.1 for the ocean and sea ice but do not assimilate ice thickness data. Another set of forecasts are initialized from the same GOFS 3.1 fields but with sea ice thickness derived from CryoSat-2 (CS2). The Navy ESPC ensemble mean September 2018 minimum sea ice extent initialized with GOFS 3.1 ice thickness was over-predicted by 0.68 M sq.km (5.27 M sq.km) versus the ensemble set of forecasts initialized with CS2 ice thickness that had an error of 0.40 M sq.km (4.99 M sq.km), a 56% reduction in error. The September mean Integrated Ice Edge Error (IIEE) shows a 19% improvement for the entire Arctic with the CS2 data versus the control run. Comparison against Upward Looking Sonar (ULS) ice thickness in the Beaufort Sea reveals a lower bias and RMSE with the CS2 forecasts at all three moorings. Ice concentration at these locations is also improved, but neither set of experiments show ice free conditions as observed at moorings A and D.

time-lagged ensembles↗