Engineering Papers⌕ Search

Engineering topics

Curtis, Nathan

Publications and source records attributed to Curtis, Nathan.

13 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Path towards Plasma Facing Components: A Review of State-of-the-art in W-Based Refractory High-Entropy Alloys

Developing advanced materials for plasma-facing components (PFCs) in fusion reactors is a crucial aspect for achieving sustained energy production. Tungsten (W) - based refractory high-entropy alloys (RHEAs) have emerged as promising candidates due to their superior radiation tolerance and high-temperature strength. This review paper will focus on recent advancements in W-based RHEA research, particularly emphasizing the key role of modelling using machine learning (ML) in the stage of discovery by predicting properties for each composition and expediting the identification of optimal RHEA compositions with desired properties. Additionally, the application of additive manufacturing (AM) techniques for fabricating W-based RHEAs is explored, highlighting their advantages for rapid prototyping and multi-compositional sample production in a high throughput manner. The review critically evaluates the current understanding of mechanical properties relevant to PFC applications, including high-temperature strength and ductility. Furthermore, the radiation tolerance of W-based RHEAs under irradiated conditions is discussed. Finally, the validity of current AM-manufactured W-based RHEAs as PFC materials is assessed, and key challenges and opportunities for future research are identified. This review aims to provide a comprehensive overview of W-based RHEAs for fusion applications and their potential to guide the development and validation of advanced refractory high entropy alloys.

Hatler, Caleb [University of Wisconsin-Madison]↗
NASA NTRS2020

Quantifying Spatial Separation Error in Tropospheric Wind Measurements

Wind measurements from the surface through the troposphere are an important asset for both range and Day of Launch (DOL) operations. Weather balloons have long been used to fulfill this operational need. Decker (2017) found balloons at Kennedy Space Center (KSC) can drift as far as 200 km from the launch site. Curtis et al. (2019) found Root Mean Square (RMS) wind deltas between 0.5 m/s and 6.3 m/s for separations between 30 km and 200 km from KSC using the North American Regional Reanalysis (NARR) model. The purpose of this study is to validate the model-based results found in Curtis et al. (2019) with observed wind and separation deltas calculated between the NASA Tropospheric Doppler Radar Wind Profiler (TDRWP) and weather balloons.

Curtis, Nathan↗
NASA NTRS2019

Analyses of Kennedy Space Center Tropospheric Doppler Radar Wind Profiler Data for Space Launch System Program Certification

This paper documents the methodology and results of analyses used to certify the Kennedy Space Center (KSC) Tropospheric Doppler Radar Wind Profiler (TDRWP) as input to launch commit evaluations for the National Aeronautics and Space Administration’s (NASA) Space Launch System Program (SLSP). These analyses, and the requirements that they address, were designed by the Marshall Space Flight Center Natural Environments Branch (MSFC NE) to certify that the TDRWP provides data of sufficient accuracy and resolution for SLSP, and that the instrument provides enough reliability to support Day-of- Launch Initialization Loads Update (DOLILU) operations. On day-of-launch (DOL), space launch vehicle operators have used data from wind profilers to reverse a previous GO call in prelaunch loads and trajectory assessments due to the profiler’s capability to quickly identify changes in the wind profile within a rapidly changing wind environment. Certification of the TDRWP would allow SLSP to use DOL wind data generated by the TDRWP to design the vehicle trajectory and to verify trajectory and load constraints during the countdown for launch commit decision.

Barbre, Robert E., Jr.↗
NASA NTRS2019

Analyzing Error in Balloon-Based Wind Measurements Due to Spatial Separation Using the North American Regional Reanalysis

Weather balloons have been a longstanding asset to NASA and Aerospace meteorology. Balloons are used from launch vehicle design to day-of-launch operations. One of the most valuable assets from these balloons is wind data from the surface up to 30 kilometers. Due to aloft winds, the balloons may drift downrange of the launch site and vehicle flight path. A 2017 study found balloons at Kennedy Space Center (KSC) can drift as far as 200 kilometers from the launch site (Decker 2017). To obtain robust launch vehicle wind assessments, it is highly desirable to characterize the wind environment along the flight path. This study looks into the errors associated with spatial separation of wind measurements using the North American Regional Reanalysis (NARR).

Curtis, Nathan↗
NASA NTRS2018

Examining Sub-Flash Properties of Lightning from GLM for Tracking and Intensification Characterization of Thunderstorms

Current methodologies for operational use of lightning are developed using ground-based networks. Lightning detectors measure different characteristics of the flash, thus they don't observe the same lightning event in the same manner: i.e., flash rates from NDLN (National Lightning Detection Network (R)) will typically not match flash rates from GLM (Geostationary Lightning Mapper) because each sensor is measuring different characteristics (EM (Electromagnetic) radiation vs. optical). Resolution/timeliness of space-based sensor data will change our "rules of thumb" for operational use: Lightning safety - how does the 2D mapping of lightning enhance lightning safety metrics; Is the super-fast input of data (20s) useful for decision-makers, including (non-AWIPS (Advanced Weather Interactive Processing System) -users) non-mets?

lightning jump↗
NASA NTRS2018

An Analysis of the Lightning Jump Algorithm Using Geostationary Lightning Mapper Flashes

Lightning's relation to severe weather has been studied since the 1980's. The invention of the Lightning Mapping Array allowed for total lightning measurements in a 125 km operational range. This brought forth an automated lightning Jump Algorithm (LIA) that predicted severe weather based on two-sigma increases in total lightning. The LIA's biggest downfall is being restrained to the limited field of view (FOV) of LMA's. The launch of the Geostationary Lightning Mapper (GLM) aboard the GOES-16 satellite now gives us hemispheric total lightning measurements. The wide FOV makes the GLM a good candidate to apply the LIA to. However the GLM and LMA have some differences. One being the coarser spatial resolution of GLM. Another being that LMA measures very high frequency (VHF) electromagnetic radiation while GLM measures optical radiation. These differences suggest an extensive study must be done on using the LIA with GLM to understand potential differences in the LIA and to maximize its operational skill. Four deep dive cases are conducted showcasing the differences between the GLM and LMA and their jumps.

Curtis, Nathan↗
NASA NTRS2018

An Analysis of the Lightning Jump Algorithm Using Geostationary Lightning Mapper Flashes

This project aims to implement the two-sigma lightning jump algorithm (LJA) developed using Lightning Mapping Arrays (LMAs), with GOES-16 Geostationary Lightning Mapper (GLM) flashes, evaluate its performance, and identify any needed adjustments to the algorithm to optimize operational skill. The GLM is projected to have lower detection efficiency (DE) (70-90 percent) than operational LMAs (95-99 percent). The reduced GLM DE coupled with the coarser spatial resolution of the GLM could have impacts on flash rates and trends that could affect the LJA in various ways. Deep dives are conducted on four separate cases. Three of four cases show LMAs seeing two to three times as many flashes as the GLM. Only fifteen of twenty five GLM jumps saw increases in radar intensity while fourteen of nineteen LMA jumps did. These results suggest a larger sample sized study must be conducted to determine how to implement the LJA with the GLM.

Curtis, Nathan↗