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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

The Role of Olivine in Fe-Carbonate Formation in Gale Crater, Mars

Carbonates have been identified in remote sensing datasets, martian meteorites, and in-situ with rovers at Gale and Jezero craters. In Gale crater, traces of carbonate have been found by the SAM instrument throughout the Mars Science Laboratory mission, e.g., at Rocknest and Pahrump Hills, with models for carbonate formation at Pahrump Hills explored by [9]. Further up-section, CheMin data of clay-rich Glen Torridon (GT) samples show that five out of seven drill samples from GT contain Fe-carbonate alongside phyllosilicates. The GT sediments were deposited in a lacustrine environment and subsequently underwent multiple episodes of diagenesis. In this work, we explore the role of olivine in the formation of carbonates by modelling the interaction of different martian olivines with a previously modeled Gale groundwater. We then explore the incongruent dissolution of host rocks within the GT sediments by mixing olivine with quantities of the Kilmarie drill sample chemical composition as the reactant rock.

S M R Turner↗
NASA NTRS2022

X-Ray Amorphous Sulfur-Bearing Phases in Sedimentary Rocks of Gale Crater, Mars

The Curiosity rover in Gale crater is investigating a mineral transition observed from orbit—an older “clay unit” to a younger “sulfate unit”—hypothesized to reflect the aridification of Mars' climate. Below this transition, the rover detected crystalline Ca-sulfates with minor Fe-sulfates but also found that some fraction of a rock's bulk SO 3 is often in the poorly constrained X-ray amorphous component. Here, we characterize the abundances and compositions of the X-ray amorphous sulfur-bearing phases in 19 drilled samples using a mass balance approach, and in a subset of 5 samples using evolved SO 2 gas measured using the SAM instrument. We find that ∼20–90 wt% of a sample's bulk SO 3 is in the X-ray amorphous state and that X-ray amorphous sulfur-bearing phase compositions are consistent with mixtures of Mg-S, Fe-S, and possibly Ca-S phases, likely sulfates or sulfites. These phases reside in the bedrock, perhaps as cementing agents deposited with detrital sediments or during early diagenesis, and in diagenetic alteration halos deposited after lithification during late diagenesis. The likely presence of highly soluble Mg-sulfates in the rocks suggests negligible fluid flow through the bedrock post-Mg-sulfate deposition. The X-ray amorphous sulfur-bearing phases probably became amorphous through dehydration in the current Martian atmosphere or inside the CheMin instrument. X-ray amorphous sulfur-bearing materials likely contribute to orbital spectral detections of sulfates, and so our results help form multiple hypotheses to be tested in the sulfate unit and are important for understanding the evolution of the Martian surface environment at Gale crater.

R. J. Smith↗
NASA NTRSDate not supplied

Overview of Mars Sample Return – Earth Entry System Woven Roughness Heating Augmentation Test in NASA Langley’s Mach 6 Wind Tunnel

The Mars Sample Return Mission (MSR) is a planned NASA flagship mission in which a sample retrieval lander (SRL) with a rover will be flown to Mars to obtain sample tubes on the surface that were dropped by the Mars 2020 rover [1]. After obtaining the sam-ples, the rover will return and ascend back to Martian orbit onboard the Mars Ascent Vehicle (MAV). Upon return to Earth orbit, the samples will perform Entry, Descent, and Landing (EDL) with the Earth Entry Sys-tem (EES) architecture, and land in Utah. The EES vehicle will utilize a HEEET-variant as its TPS, which will be the first time a woven TPS will be used on a flagship NASA mission [2]. This TPS offers a unique challenge for Computational Fluid Dynamics (CFD) modeling of the aerothermal envi-ronment of the vehicle, as woven roughness heating augmentation has not been extensively investigated experimentally. As a result, in order to validate com-putational models for woven roughness heating aug-mentation, a wind tunnel test campaign at NASA Langley Research Center’s Mach 6 wind tunnel was performed in April of 2023. This test campaign consisted of over a hundred runs with Reynolds numbers spanning from 1-7 mil-lion 1/ft and with six separate wind tunnel models used. A second campaign with a suite of new models will be conducted in Summer 2023 as well as a cam-paign with a flat plate model, both of which are of great interest to the MSR-EES project. The data obtained from this test are extremely vital for the MSR mission, as they will validate CFD roughness heating models which will be directly used to design the TPS of the EES portion of MSR and characterize the heating environment that the entry ve-hicle will experience. Further extensions of the MSR-EES test campaign will continue to provide validation data for developing more effective computational tools.

Jonathan Cheatwood↗
NASA NTRSDate not supplied

Evidence for Partially Chloritized Smectite in Gale Crater, Mars, and Implications for Diagenesis

Phyllosilicates are an important mineral group found in ancient (~3.5-4.1 Gyr old) martian terrains because they are a marker of water-rock interactions and can help constrain aqueous conditions (e.g., pH, salinity, temperature) and, thus, identify habitable environments. Orbital visible/short-wave infrared (VSWIR) data demonstrate that smectite is the most abundant type of phyllosilicate on Mars, followed by chlorite [e.g., 1]. The geologic settings in which phyllosilicates are found provide important clues into their formation. Smectite has been identified in abundances of up to ~30 wt.% in early Hesperian-aged fluvial-lacustrine sedimentary rocks in Gale crater using the CheMin X-ray diffractometer on the Mars Science Laboratory Curiosity rover [e.g., 2-6]. CheMin XRD patterns and evolved water measured by the Sample Analysis at Mars (SAM) instrument suite show the structure of smectite changes from trioctahedral Fe(II)-bearing smectite at the base of the section to dioctahedral nontronite and montmorillonite ~400 m up section in the Glen Torridon valley where orbital VSWIR show evidence of Fe/Mg smectite. Most of the smectite identified by CheMin is collapsed (i.e., lacking substantial interlayer H2O) based on basal spacings at 10 Å. Fe(II) saponite found in two drill targets at the base of the section in Yellowknife Bay, however, suggest the smectite is expanded. The XRD pattern of the “Cumberland” drill target has a peak at 13.5 Å, whereas the “John Klein” drill target has a peak at 10 Å and a shoulder extending to higher d-spacings (Fig. 1) [2]. A possible explanation for this expanded structure is partial chloritization of the interlayer site caused by the precipitation of small domains of brucite-like sheets [e.g., 7,8]. Here, we synthesize smectite with different degrees of chloritization and analyze the products via XRD, evolved gas analysis (EGA), and VSWIR to determine whether chloritized smectite on Mars can be recognized with these techniques.

E B Rampe↗
NASA NTRSDate not supplied

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

Introduction The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗
NASA NTRSDate not supplied

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗
NASA NTRSDate not supplied

Evaluation Marcelling in Composites using Ultrasonic Guided Wave

Thermoplastic composite (TPC) material seldom manifests in-plane fiber waviness during manufacturing. In-plane fiber waviness is called marcelling. Marcelling com-promises the composite strength and performance. When present in a structure, marcelling is not only a surface defect but can extend partially along the thickness of the composite. There is no established nondestructive evaluation (NDE) method to detect and quantify marcelling in composite. Ultrasonic guided waves can saturate the complete thickness of a composite structure. Thus, physics of guided wave creates an opportunity to detect and quantify the marcelling in composites. Before guided waves could be used to detect marcelling, it is necessary to quantify the marcelling in the structure and identify the marcelling affected zones (MAZE). In this research first, high frequency scanning acoustic microscopy (SAM) was performed to quantify the marcelling and statistical distribution of the defects at different MAZE was obtained. Next the MAZE with known statistical distribution of quantified marcelling (marcelling wavelength and marcelling amplitude) was inspected using ultrasonic guided wave setup. The method quantified the guided wave feature as a function of quantitative degree of marcelling. The overarching objective of this research is to implement post process NDE inspection of TPC large structures where in plane fiber waviness or marcelling can be detected and MAZEs could be identified. Primary fining is that the reduction of wave velocity and amplitude of ultrasonic guided wave could be good indicators of MAZE. However, more rigorous calibration is necessary where inspection direction is carefully devised with respect to the marcelling.

HiCAM↗
NASA NTRS2024

Comparison of Multisine Peak Factor Minimization Algorithms for Aircraft System Identification

Two phase-optimized multisine peak factor minimization algorithms are presented and evaluated. The first algorithm minimizes peak factor by iteratively clipping the peaks of generated multisine signals. The second algorithm optimizes peak factor indirectly through minimization of an approximation of the infinity norm of the multisine. Algorithm performance was evaluated as a function of different signal properties, including the number of harmonics, harmonic spacing, and number of snow harmonics (extra harmonics included for further reduction of the peak factor). The two algorithms are compared against results obtained by minimizing peak factor directly using a simplex algorithm, which has been a common approach when designing phase-optimized multisines for system identification flight tests. Sample results show that the clipping and infinity norm algorithms produced multisine signals with comparable peak factors that were lower than that of the simplex algorithm. However, the clipping algorithm runs an order of magnitude faster than the other two algorithms, which also makes it practical to repeat the algorithm multiple times to achieve even lower peak factors.

system identification↗
NASA NTRSDate not supplied

Comparison of Multisine Peak Factor Minimization Algorithms for Aircraft System Identification(Presentation)

Two phase-optimized multisine peak factor minimization algorithms are presented and evaluated. The first algorithm minimizes peak factor by iteratively clipping the peaks of generated multisine signals. The second algorithm optimizes peak factor indirectly through minimization of an approximation of the infinity norm of the multisine. Algorithm performance was evaluated as a function of different signal properties, including the number of harmonics, harmonic spacing, and number of snow harmonics (extra harmonics included for further reduction of the peak factor). The two algorithms are compared against results obtained by minimizing peak factor directly using a simplex algorithm, which has been a common approach when designing phase-optimized multisines for system identification flight tests. Sample results show that the clipping and infinity norm algorithms produced multisine signals with comparable peak factors that were lower than that of the simplex algorithm. However, the clipping algorithm runs an order of magnitude faster than the other two algorithms, which also makes it practical to repeat the algorithm multiple times to achieve even lower peak factors.

flight test↗
DOE OSTI2020

Understanding Bifacial PV Modeling: Raytracing and View Factor Models

As part of the PV Magazine Webinar 'View-factor vs. ray tracing - which bifacial modelling techniques should you use?,' the second part lead by NREL will explore the different rear-irradiance calculation software, which fall into two categories: view-factor and ray-tracing models. View factor models assume isotropic scattering of reflected rays, allowing for calculation of irradiance by integration. Due-diligence software such as PVSyst or SAM use the view-factor model. Ray-tracing models simulate multipath reflection and absorption of individual rays entering a scene. Raytracing software such as bifacial_radiance, which is the only available open-source toolkit, offers the possibility of reproducing complex scenes, including shading or finite-system edge effects. This can be useful to evaluate specific system geometries, shading and obstructions, areas of different albedo and electrical mismatch, all topics of interest to the prediction of bifacial performance. Model agreement for view factors and bifacial_radiance software is improving and has been shown to be between 2% (absolute) when compared with measured results.

14 SOLAR ENERGY↗
DOE OSTI2021

Renewable Thermal Hybridization Framework for Industrial Process Heat Applications

Renewable thermal energy systems (RTES) could be hybridized with different renewable options (e.g., flat plate collectors (FPCs) with parabolic collectors), or combined with existing heat supplies (e.g., fossil fuels), to give options for targeted solar IPH applications, industrial decarbonization and the reduction of fuel consumption. Buildings and industrial thermal energy applications require different temperature ranges, quantities, and rates of thermal energy, and as such require flexible, cost competitive solutions, able to provide heat over various temperature ranges. Hybrid solutions and thermal energy storage (TES) will be important for the dispatch of heat at optimal times needed by the demand side of the buildings and industrial applications. A variety of tools and platforms, such as the System Advisor Model (SAM), can provide hourly thermal yield simulations from single renewable energy (RE) technology options, including FPCs or CSP for solar IPH. We have investigated a variety of approaches to hybrid system modeling for RTES at different temperatures or combinations of technologies and developed an initial framework. The hybridization framework starts by creating a heat stream and raising the temperature of that heat stream by various combinations of RE technologies and other sources such as fossil fuels, new fuels or electric heating in multiple stages, with options for TES and/or waste heat recovery (WHR).

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Evaluation of Low-Pressure-Sintered Multi-Layer Substrates for Medium-Voltage SiC Power Modules: Preprint

Direct-bonded aluminum (DBA) multi-layer substrates have been fabricated using low-pressure silver sintering. These multi-layer substrates can be used to reduce the peak electric field strength inside power modules. This benefit is particularly important for medium-voltage silicon carbide (SiC) MOSFETs due to their higher operating voltages. The voiding content and defect density of the bond used to create the multi-layer substrate stackup is critical to the thermal performance and reliability of the power module. This work two low-pressure-assisted sintering techniques; one using nano-silver preform and the other using nano-silver paste to bond 23 mm by 49 mm DBA substrates. Scanning acoustic microscopy (C-SAM) is used to evaluate the bond quality after sintering. To evaluate the reliability of the sintered multi-layer substrates, passive thermal cycling from –40 °C to 200 °C was performed. Cross-sections were cut at pre-determined intervals and imaged with Scanning Electron Microscopy (SEM). After 1,000 thermal cycles, minor cracking was observed, but no failures have occurred.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2021

Marine Energy Performance Models

This webinar was presented on August 18, 2021 and provides an overview of SAM's marine wave and tidal energy models.

ENERGY PLANNING, POLICY, AND ECONOMY,TIDAL AND WAV↗
DOE OSTI2021

Host cells and methods for producing toluene biochemically

The present invention provides for a genetically modified host cell comprising a first polypeptide comprising a sequence having at least 70% amino acid sequence identity with a phenylacetate decarboxylase, and having an enzymatic activity to decarboxylate a phenylacetic acid into a toluene and a carbon dioxide, and a second polypeptide comprising a sequence having at least 70% amino acid sequence identity with a phenylacetate decarboxylase activating enzyme, and having an enzymatic activity to cleave a S-adenosylmethionine (SAM) to form a methionine and a 5′-deoxyadenosyl radical.

Beller, Harry R.↗
DOE OSTI2022

Concentrated Solar Power as a Pathway for Electrolytic Hydrogen Production

William Xi and Mark Ruth of the National Renewable Energy Laboratory (NREL), will present a new solar-electrolysis technoeconomic assessment capability: low-temperature and high-temperature electrolysis in the System Advisor Model (SAM) environment. They will also present analysis results including opportunities for solar-hydrogen systems to achieve the $2/kg hydrogen cost target.

concentrating solar power↗
DOE OSTI2022

Value Proposition of UV-Absorbers in PV Module Encapsulation

Various common crystalline silicon cell technologies were exposed to UVA radiation (1.24 Wm-2 nm-1 at 340 nm peak) on the front and back faces at 45 degrees Celsius for periods up to 3000 h, representing about 3 y of solar exposure in Phoenix, Arizona, USA. The resulting degradation of the open-circuit voltage and short-circuit current is presented. Of the various cell types examined, significant levels of degradation were seen in all cases. Less degradation was generally found after UV irradiation of cell fronts and older cell types, whereas a bifacial PERC type exposed on the rear showed about 25% degradation in short circuit current, attributable to lack of a diffused surface field. Selected cells were exposed to UV irradiation with the addition of long pass UV filters to replicate UV-absorbers in encapsulants. Modern cell designs are sensitive to UV-ID because of reduced or eliminated front and back surface field and increased dependence on high quality surface passivation. Single transformation of the independent variable (t, kW h/m^2) could be used to achieve a linear model of the data to extrapolate to 50 y. Solar Advisor Model (SAM) shows appropriate filtering of UV-irradiation can improve LCOE and net present value of plant. Some advanced cell types are seen to be UV-resistant (cell level solutions also exist). Solutions therefore exist on the cell, glass, and encapsulant level. Changes over time in each of these would also need to be considered (solarization, encapsulant browning...).

ENGINEERING,SOLAR ENERGY↗
DOE OSTI2023

Uncertainty Quantification of PV Annual Energy Estimates in the System Advisor Model

This work will detail a proposed uncertainty quantification method for PV annual energy estimates. Motivations behind the proposed methodology will be discussed, including the frequent underperformance of installed PV systems to calculated probability of exceedance values being seen in industry. A methodology in which uncertainty factors correlated to different parts of the PV annual energy model chain are applied to annual energy estimates in conjunction with uncertainty from inter-annual solar resource variability will be described. The application of this methodology in the System Advisor Model (SAM) will also be discussed with example cases and graphical outputs of the probability of exceedance data calculated for the PV annual energy estimates.

energy modeling↗