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NASA NTRS1994

Replicate Wolter-I x-ray mirrors

Cylindrical (hyperbolic - parabolic Wolter I) mirrors have been electroformed from nickel over an electroless nickel-phosphorous (NiP) plated aluminum mandrel in support of the NASA AXAF-S x-ray spectrometer program. The electroless nickel was diamond turned and polished to achieve a surface finish of 10 angstroms rms or better. Gold was then plated on the nickel alloy after an electrochemical passivation step. Next a heavy layer of pure nickel was plated one millimeter thick with controlled stress at zero using a commercial PID program to form the actual mirror. This shell was removed from the NiP alloy coated mandrel by cryogenic cooling and contraction of the aluminum to release the mirror. It is required that the gold not adhere well to the NiP but all other plated coatings must exhibit good adherence. Four mirrors were fabricated from two mandrels prepared by this method. The area of each part is 0.7 square meters (7.5 square feet).

Engelhaupt, D. E.↗

NASA NTRS2003

Calibration of Passive Microwave Hybrid Coupler-based Polarimeters

Passive microwave polarimeters, or polarimetric radiometers, are important tools for Earth remote sensing. They have found utility in ocean surface wind-vector remote sensing and polarization basis rotation systems for compensating instrument or ionospheric induced rotation. The hybrid coupler-based polarimeter is a specific class of polarimeter that utilizes a 180-degree hybrid coupler to affect a correlation between the received vertical and horizontal polarization signals. This type of polarimeter requires at least four calibration states for complete calibration. One state must be a polarized signal, such as the application of a correlated noise source. The phase balance of the noise source directly determines the quality of the calibration.

Piepmeier, J. R.↗

NASA NTRS2007

A Synopsis of Interfacial Phenomena in Lithium-Based Polymer Electrolyte Electrochemical Cells

The interfacial regions between electrode materials, electrolytes and other cell components play key roles in the overall performance of lithium-based batteries. For cell chemistries employing lithium metal, lithium alloy or carbonaceous materials (i.e., lithium-ion cells) as anode materials, a "solid electrolyte interphase" (SEI) layer forms at the anode/electrolyte interface, and the properties of this "passivating" layer significantly affect the practical cell/battery quality and performance. A thin, ionically-conducting SEI on the electrode surface can beneficially reduce or eliminate undesirable side reactions between the electrode and the electrolyte, which can result in a degradation in cell performance. The properties and phenomena attributable to the interfacial regions existing at both anode and cathode surfaces can be characterized to a large extent by electrochemical impedance spectroscopy (EIS) and related techniques. The intention of the review herewith is to support the future development of lithium-based polymer electrolytes by providing a synopsis of interfacial phenomena that is associated with cell chemistries employing either lithium metal or carbonaceous "composite" electrode structures which are interfaced with polymer electrolytes (i.e., "solvent-free" as well as "plasticized" polymer-binary salt complexes and single ion-conducting polyelectrolytes). Potential approaches to overcoming poor cell performance attributable to interfacial effects are discussed.

Baldwin, Richard S.↗

NASA NTRS2009

A Comparison of Surface Acoustic Wave Modeling Methods

Surface Acoustic Wave (SAW) technology is low cost, rugged, lightweight, extremely low power and can be used to develop passive wireless sensors. For these reasons, NASA is investigating the use of SAW technology for Integrated Vehicle Health Monitoring (IVHM) of aerospace structures. To facilitate rapid prototyping of passive SAW sensors for aerospace applications, SAW models have been developed. This paper reports on the comparison of three methods of modeling SAWs. The three models are the Impulse Response Method a first order model, and two second order matrix methods; the conventional matrix approach, and a modified matrix approach that is extended to include internal finger reflections. The second order models are based upon matrices that were originally developed for analyzing microwave circuits using transmission line theory. Results from the models are presented with measured data from devices.

Wilson, W. c.↗

NASA NTRS2012

The NASA Soil Moisture Active Passive (SMAP) Mission - Science and Data Product Development Status

The Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has the objective of frequent, global mapping of near-surface soil moisture and its freeze-thaw state. The SMAP measurement system utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The instruments will operate on a spacecraft in a 685 km polar orbit with 6am/6pm nodal crossings, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments will yield global maps of soil moisture and freeze/thaw state at 10 km and 3 km resolutions, respectively, every two to three days. The 10-km soil moisture product will be generated using a combined radar and radiometer retrieval algorithm. SMAP will also provide a radiometer-only soil moisture product at 40-km spatial resolution and a radar-only soil moisture product at 3-km resolution. The relative accuracies of these products will vary regionally and will depend on surface characteristics such as vegetation water content, vegetation type, surface roughness, and landscape heterogeneity. The SMAP soil moisture and freeze/thaw measurements will enable significantly improved estimates of the fluxes of water, energy and carbon between the land and atmosphere. Soil moisture and freeze/thaw controls of these fluxes are key factors in the performance of models used for weather and climate predictions and for quantifYing the global carbon balance. Soil moisture measurements are also of importance in modeling and predicting extreme events such as floods and droughts. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. In the Testbed algorithms are developed and evaluated using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including data from the SMOS and Aquarius missions. We report here on the development status of the SMAP data products. The Testbed simulations are designed to capture various sources of errors in the products including environment effects, instrument effects (nonideal aspects of the measurement system), and retrieval algorithm errors. The SMAP project has developed a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level l) and derived geophysical products (Level 2 and higher).

Nloku, E.↗

NASA NTRS2013

Evaluation of Nanomaterial Approaches to Damping in Epoxy Resin and Carbon Fiber/Epoxy Composite Structures by Dynamic Mechanical Analysis

Vibration mitigation in composite structures has been demonstrated through widely varying methods which include both active and passive damping. Recently, nanomaterials have been investigated as a viable approach to composite vibration damping due to the large surface available to generate energy dissipation through friction. This work evaluates the influence of dispersed nanoparticles on the damping ratio of an epoxy matrix. Limited benefit was observed through dispersion methods, however nanoparticle application as a coating resulting in up to a three-fold increase in damping.

Miller, G.↗

NASA NTRS2015

CALIPSO-Inferred Aerosol Direct Radiative Effects: Bias Estimates Using Ground-Based Raman Lidars

Observational constraints on the change in the radiative energy budget caused by the presence of aerosols, i.e. the aerosol direct radiative effect (DRE), have recently been made using observations from the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO). CALIPSO observations have the potential to provide improved global estimates of aerosol DRE compared to passive sensor-derived estimates due to CALIPSO's ability to perform vertically-resolved aerosol retrievals over all surface types and over cloud. In this study we estimate the uncertainties in CALIPSO-inferred aerosol DRE using multiple years of observations from the Atmospheric Radiation Measurement (ARM) program's Raman lidars (RL) at mid-latitude and tropical sites. Examined are assumptions about the ratio of extinction-to-backscatter (i.e. the lidar ratio) made by the CALIPSO retrievals, which are needed to retrieve the aerosol extinction profile. The lidar ratio is shown to introduce minimal error in the mean aerosol DRE at the top-of-atmosphere and surface. It is also shown that CALIPSO is unable to detect all radiatively-significant aerosol, resulting in an underestimate in the magnitude of the aerosol DRE by 30â€"50%. Therefore, global estimates of the aerosol DRE inferred from CALIPSO observations are likely too weak.

Thorsen, Tyler↗

NASA NTRS2016

CALIPSO-Inferred Aerosol Direct Radiative Effects: Bias Estimates Using Ground-Based Raman Lidars

Observational constraints on the change in the radiative energy budget caused by the presence of aerosols, i.e. the aerosol direct radiative effect (DRE), have recently been made using observations from the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO). CALIPSO observations have the potential to provide improved global estimates of aerosol DRE compared to passive sensor-derived estimates due to CALIPSO's ability to perform vertically-resolved aerosol retrievals over all surface types and over cloud. In this study we estimate the uncertainties in CALIPSO-inferred aerosol DRE using multiple years of observations from the Atmospheric Radiation Measurement (ARM) program's Raman lidars (RL) at midlatitude and tropical sites. Examined are assumptions about the ratio of extinction-to-backscatter (i.e. the lidar ratio) made by the CALIPSO retrievals, which are needed to retrieve the aerosol extinction profile. The lidar ratio is shown to introduce minimal error in the mean aerosol DRE at the top-of-atmosphere and surface. It is also shown that CALIPSO is unable to detect all radiatively-significant aerosol, resulting in an underestimate in the magnitude of the aerosol DRE by 30-50%. Therefore, global estimates of the aerosol DRE inferred from CALIPSO observations are likely too weak.

Thorsen, Tyler↗

NASA NTRS2016

Investigating the Feasibility of Utilizing Carbon Nanotube Fibers for Spacesuit Dust Mitigation

Historical data from the Apollo missions has compelled NASA to identify dust mitigation of spacesuits and other components as a critical path prior to sending humans on potential future lunar exploration missions. Several studies thus far have proposed passive and active countermeasures to address this challenge. However, these technologies have been primarily developed and proven for rigid surfaces such as solar cells and thermal radiators. Integration of these technologies for spacesuit dust mitigation has remained an open challenge due to the complexity of suit design. Current research investigates novel methods to enhance integration of the Electrodynamic Dust Shield (EDS) concept for spacesuits. We leverage previously proven EDS concept developed by NASA for rigid surfaces and apply new techniques to integrate the technology into spacesuits to mitigate dust contamination. The study specifically examines the feasibility of utilizing Carbon Nanotube (CNT) yarns manufactured by Rice University as electrodes in spacesuit material. Proof of concept testing was conducted at NASA Kennedy Space Center using lunar regolith simulant to understand the feasibility of the proposed techniques for spacesuit application. Results from the experiments are detailed in this paper. Potential challenges of applying this technology for spacesuits are also identified.

Electrodynamic Dust Shield↗

NASA NTRS2018

Global Assessment of the SMAP Level-4 Soil Moisture Product Using Assimilation Diagnostics

The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and related land surface variables from 31 March 2015 to present with approx. 2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of approx. 0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under approx. 3 K), the soil moisture increments (under approx. 0.01 cu m/cu m), and the surface soil temperature increments (under approx. 1 K). Typical instantaneous values are approx. 6 K for O-F residuals, approx. 0.01 (approx. 0.003) cu m/cu m for surface (root-zone) soil moisture increments, and approx. 0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.

Reichle, Rolf↗

NASA NTRS2018

Using Data Assimilation Diagnostics to Assess the SMAP Level-4 Soil Moisture Product

The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and related land surface variables from 31 March 2015 to present with approx.2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of approx. 0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under approx. 3 K), the soil moisture increments (under approx. 0.01 cu m/cu m), and the surface soil temperature increments (under approx. 1 K). Typical instantaneous values are approx. 6 K for O-F residuals, approx. 0.01 (approx. 0.003) cu m/cu m for surface (root-zone) soil moisture increments, and approx. 0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.

SMAP↗

NASA NTRS2019

Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product

The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with a mean latency of ~2.5 days. The underlying L4_SM algorithm assimilates SMAP radiometer brightness temperature (Tb) observations into the NASA Catchment land surface model using a spatially-distributed ensemble Kalman filter. Version 4 of the L4_SM modeling system includes a reduction in the upward recharge of surface soil moisture from below under non-equilibrium conditions, resulting in reduced bias and improved dynamic range of L4_SM surface soil moisture compared to earlier versions. This change and additional technical modifications to the system reduce the mean and standard deviation of the observation-minus-forecast Tb residuals and overall soil moisture analysis increments while maintaining the skill of the L4_SM soil moisture estimates versus independent in situ measurements; the average, bias-adjusted RMSE in Version 4 is 0.039 m(exp 3) m(exp -3) for surface and 0.026 m(exp 3) m(exp -3) for root-zone soil moisture. Moreover, the coverage of assimilated SMAP observations in Version 4 is near-global owing to the use of additional satellite Tb records for algorithm calibration. L4_SM soil moisture uncertainty estimates are biased low (by 0.01-0.02 m(exp 3) m(exp -3)) against actual errors (computed versus in situ measurements). L4_SM runoff estimates, an additional product of the L4_SM algorithm, are biased low (by 35 mm year (exp -1)) against streamflow measurements. Compared to Version 3, bias in Version 4 is reduced by 46% for surface soil moisture uncertainty estimates and by 33% for runoff estimates.

RMSE↗

NASA NTRS2019

Progress Toward Implementation of Coupled Ocean/Atmosphere in Unified Forward Operator (UFO)

The (Sea-Ice Ocean and Coupled Assimilation) SOCA project focuses on meshing atmospheric and marine data assimilation efforts to create innovative data assimilation systems. One of the main goals ofSOCA is to make use of surface-sensitive radiances to constrain sea-ice and upper ocean fields (e.g., salinity, temperature, sea-ice fraction, sea-ice temperature, etc.). the focus of this research is to build first elements toward an ocean/sea-ice/atmosphere coupled data assimilation capability, with a focus on supporting and developing the assimilation of observations sensitive to multiple sub-domains. We Setup the existing Joint Effort for Data assimilation Integration (JEDI) coupled UFO (CRTM related) for surface sensitive microwave radiances (SST and SSS) focusing on Global Precipitation Measurement (GPM) Imager (GMI) and Soil Moisture Active Passive (SMAP).

Ebrahimi, Hamideh↗

NASA NTRSDate not supplied

Engineering Polymers as Structural Materials in Spacecraft Water Systems

The novel application of structural materials, surface treatments, and barrier coatings is desired to mitigate the rapid loss of ionic silver (Ag+) biocide observed with passive metal alloys, improve reliability, and reduce system mass. In this work, we provide an initial look at the potential replacement of these heritage alloys in spacecraft water systems with high-performance thermoplastic engineering polymers, including PEEK, PEI, and PVDF. Such materials have found increasing use as structural materials in a broad array of performance-critical applications, including in the aerospace, medical implant, and chemical processing fields. We selected a number of promising materials for investigation, compiled mechanical behavior data, and conducted theoretical performance analyses. We also identified and began to address numerous material suitability concerns as well as design requirements for pressurized components in human-rated spacecraft hardware. These include material flammability, offgassing, leaching, chemical resistance, radiation tolerance, prevention of fracture/yielding, and others. We find that there is significant potential for use of engineering polymers in spacecraft water systems, and suggest some directions for future research.

Lance Dean Delzeit↗

NASA NTRS2020

Integrated Silicon Platform for Co-planar Design of Vertically Stacked 2.06 THz Mixer Module

The process for fabricating and utilizing the threedimensional Si stack receiver front-end is described in this paper. The capability to have exact dimensionality becomes essential as frequency scales due to the complexity arising in assembly and finer tolerances. Total process yields can be improved through Si fabrication by verifying achievement of specified tolerances lithographically and compatibility to rapid process changes and design fine-tuning. The integrated Si platform with the mounted device is shown in Figure 1. Signal I/O and alignment modalities enable lownoise measurements. Silicon micromachining provides the necessary accuracy for integration at the several THz regime. Particularly, processing and etch recipes have demonstrated smooth surfaces of < 1 μm surface roughness. In consideration is pre-compensating for minute offsets, matching mechanical strain on all interfaces, and including passive alignment verification in the design. As compared to metal blocks, computer numerical controlled (CNC) milling can produce slight burrs in the interfaces resulting in misalignment and resultant strain between two pieces of components. Furthermore, Si integration can make possible arrays of pixel transceivers through compact subsystems for the purpose of measuring multiple lines of spectral content simultaneously in space.

Mehdi, Imran↗

NASA NTRSDate not supplied

Examination of L-Band Brightness Temperature Forecasts in the SMAP Level-4 Soil Moisture Analysis

The NASA Soil Moisture Active Passive (SMAP) mission [4] has been providing L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations since April 2015. By assimilating the Tb observations into the NASA Catchment land surface model [5] using a spatially distributed ensemble Kalman filter, the NASA Global Modeling and Assimilation Office generates the SMAP Level-4 Soil Moisture (L4_SM) product, which provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with ~2.5-day latency for use in research and applications [6]. The L4_SM product also includes estimates of soil temperature, land surface fluxes, and assimilation diagnostics such as the model forecast and observed Tb values [7]. The output from the L4_SM system is routinely monitored by the L4_SM team. Such monitoring provides valuable information; instances of unusually large Tb observation-minus-forecast (O-F) residuals can indicate events during which soil moisture conditions are poorly described in the land modeling system [7,8]. For example, repeated occurrences of very large Tb O-F values in central Australia were traced back to deficiencies in the gauge-based precipitation product used in the land modeling system through L4_SM Version 5; this discovery prompted the use, beginning in Version 6, of satellite- and gauge-based precipitation observations outside of North America [9]. Recently, a statistical analysis of the Tb O-F residuals revealed systematic errors in the “tau-omega” L-band radiative transfer model that converts the land-model simulated soil moisture and temperature into the forecast Tb prior to the L4_SM analysis. The L4_SM analysis is built on the ensemble Kalman filter and assumes unbiased forecast errors. The presence of systematic Tb forecast errors could thus adversely impact the quality of the analyzed soil moisture. In this paper, we examine the Tb O-F residuals of the latest Version 7 L4_SM data (Science Version ID Vv7030 and Vv7032) [10,11,12]. In the L4_SM Version 7 algorithm, key parameters of the L-band radiative transfer model, including soil roughness, scattering albedo, and a (seasonally varying) climatology of vegetation opacity, are obtained from the SMAP Level-2 Radiometer retrieval product (Version 5) [1]. Additionally, we also use ground measurements of surface soil moisture and soil temperature from the SMAP core validation sites as in situ reference of soil conditions [2,3]. As part of the L4_SM system calibration, the seasonally-varying bias between the model forecast Tb and the observed values is removed prior to the assimilation of the SMAP Tb observations [7]. That is, the L4_SM system is designed to only correct errors in synoptic-scale and interannual variations from the long-term mean seasonal cycle while maintaining the model’s (potentially erroneous) climatology. The Tb O-F residuals examined here are thus computed using SMAP Tb observations after they are rescaled to the mean seasonal cycle of Tb from the modeling system without SMAP data assimilation. Consequently, the long-term average of the Tb O-F residuals has a global mean of only 0.13 K and locally small values, ranging from -1 to 3 K. Despite the small time-average values of the Tb O-F residuals, the model forecast Tb was nevertheless found to exhibit undesirable systematic errors. At some locations, the time-average Tb O-F values strongly depend on surface soil moisture (SM). At the Yanco SMAP core validation site, for example, the Tb O-F residuals typically range from 5 to 15 K under dry soil moisture conditions (SM < 0.15 m3 m-3) yet are predominantly negative under wet soil moisture conditions (SM > 0.25 m3 m-3), with values ranging from 0 to -40 K. This results in soil moisture analysis increments that persistently make the soil drier under dry SM conditions and persistently make the soil wetter under wet SM conditions, suggesting an error in the dynamic range of the simulated Tb, soil moisture or soil temperature. In this paper, we describe the higher-order systematic Tb forecast errors in more detail, examine their impact on the L4_SM product quality, and explore potential avenues to further improve the L4_SM algorithm.

Rolf Reichle↗

NASA NTRSDate not supplied

Total Variation Majorization Minimization (TV-MM) Approach to Radiometer Brightness Temperature Gridding and Reconstruction

This paper presents the implementation of an algorithm to enhance the image resolution of the Earth's surface brightness temperature (T B ) data measured by radiometers such as the one onboard of the Soil Moisture Active Passive (SMAP) mission. A key step in radiometer T B processing is the conversion of the swath-based calibrated antenna temperature (T A ) measurements to the Level 3 Earth-centered grid. The simplest algorithm to transform this data from swath to gridded format is called drop-in-the-bucket which simply averages surrounding noisy T A samples to form a T B value at the gridded location. This method reduces noise, however produces low resolution products. To obtain a higher resolution product, SMAP uses other techniques such the Backus-Gilbert (BG) algorithm, which is the conventional method used in microwave radiometry. Although this method performs the required interpolation, it is not effective in denoising and removing blurring effects due to antenna filtering of the radiometer image data. Our motivation for this development is to further improve the resolution through post-processing of the radiometer T B image, a highly cost-effective method of image enhancement. The approach adapted in this work is based on the minimization of the Total Variation (TV) regularized objective function that is used extensively in solving general ill-posed linear inverse problems in image processing. Since the TV-based objective function is convex but not everywhere differentiable, there exists many numerical algorithms that can estimate the solution and the one selected for this work is called Majorization- Minimization (MM). By applying this algorithm, simulation experiments were performed based on synthetic data from the Geophysical model as well as real SMAP data to demonstrate the effectiveness of the technique. Results were then compared against the BG method.

Wing Lee↗

NASA NTRSDate not supplied

Parameterized Study of Heat Load Trends in a Subscale Rotating Detonation Rocket Engine

NASA has developed a subscale rotating detonation rocket engine platform, enabling rapid parameterization of components and their associated performances. A major performance metric of interest for RDREs is the total heat absorbed at a given operating condition and wave mode operation. To investigate this, several sets of hardware were produced to have variation of the contraction ratio, injector geometry, and length. A wide range of total mass flow rates and mixture ratios were also explored using gaseous methane/oxygen. All hardware was produced using laser powder bed fusion GRCop-42, GRX-810, or C-103 alloys depending on the component cooling requirements. Outer and inner body hardware were made from GRCop-42 where heat fluxes were expected to be high and were water cooled through integrated coolant channels. Nozzles were made from C-103 which are radiatively cooled. Finally, the injectors were produced using GRCop-42 or GRX-810 as passive cooling via propellant injection has previously found to be sufficient given the small gap width of exposed injection surface. Total heat load and bulk heat flux measurements to the hot walls are reported. Trends in heat load and heat flux are shown with relation to parameters such as chamber pressure, area ratio, and wave mode. Heat loads between the inner and outer bodies and the chamber and shroud section are compared.

Heat Flux↗