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At least 1,099 records · Page 61

Space Shuttle Main Engine instrumented High Pressure Oxidizer Turbopump technology test bed testing results summary

This paper presents the test results from the Space Shuttle Main Engine (SSME) instrumented High Pressure Oxidizer Turbopump (HPOTP). The turbopump was tested on Engine 3001, a highly instrumented engine, in an effort to characterize the turbopump and the engine system. Seven tests, for a total duration of 766 seconds, were performed over a five month time period. The testing was performed at a wide variety of engine conditions. Changes in engine mixture ratio, power level, engine inlet oxidizer pressure, engine inlet fuel pressure, and engine start sequence were made. A discussion of all the HPOTP pressure and temperature data obtained are presented with comparisons to supporting analyses made where applicable. The effect of the various engine conditions on the measured data is addressed. This paper also discusses the challenges that were overcome to obtain the data. The significant instrumentation related problems encountered during the design, fabrication, and testing of this turbopump are summarized. Only those issues that affected the data obtained or the instrumentation itself are discussed. The relevance of the data to other noninstrumented turbomachinery is outlined. Conclusions and recommendations resulting from the test series will be presented.

Koelbl, Mary E.↗

Joint Modeling of Wind Speed and Wind Direction Through a Conditional Approach

Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to climate change research. It is therefore crucial to accurately estimate the joint probability distribution of wind speed and direction. In this work, we develop a conditional approach to model these two variables, where the joint distribution is decomposed into the product of the marginal distribution of wind direction and the conditional distribution of wind speed given wind direction. To accommodate the circular nature of wind direction, a von Mises mixture model is used; the conditional wind speed distribution is modeled as a directional dependent Weibull distribution via a two-stage estimation procedure, consisting of a directional binned Weibull parameter estimation, followed by a harmonic regression to estimate the dependence of the Weibull parameters on wind direction. A Monte Carlo simulation study indicates that our method outperforms two other approaches in estimation efficiency: one that utilizes periodic spline quantile regression and another that generates data from the commonly used Abe-Ley distribution for cylindrical data. We illustrate our method by using the output from a regional climate model to investigate how the joint distribution of wind speed and direction may change under some future climate scenarios. Our method indicates significant changes in the variation of wind speed with respect to some directions.

17 WIND ENERGY↗

Large spin splittings due to the orbital degree of freedom and spin textures in a ferroelectric nitride perovskite

First-principles simulations are conducted to predict that ferroelectric nitride perovskite LaWN 3 not only exhibits large spin splittings (2.7 eV Å) but also possesses unique spin textures for some of its conduction levels. Such spin splittings around the Γ and L points cannot be interpreted as a typical mixture of Rashba or Dresselhaus configurations but rather require the development of four-band $\textit{k ∙ p}$ models with high-order terms. We further identify that, for some bands, spin splittings can be greatly contributed by the pure orbital degree of freedom (PODF), a unique character of our four-band Hamiltonian compared to the traditional two-band version. The concept of PODF-enhanced spin splittings paves a way for designing materials with large spin splittings. Moreover, the energy levels possessing such large splittings and complex spin textures can be brought close to the conduction-band minimum by applying epitaxial strain.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Impurity Extraction by Droplets

The goals are to model and to measure the phase equilibrium properties of a finely divided fluid containing a large number of chemically similar species. The objective is to develop an accurate, usable model for such phenomena as pollutant extraction of rain clouds, industrial separation in spray towers, and separation in emulsions. The project was designed as a hierarchy of complementary theoretical and experimental steps. A theory was developed to describe the segregation of complex impurities at the interface of a solvent. This phenomenon is important in phase behavior when a large fraction of molecules in a material are near an interface, the situation in a finely divided material. The theory will be modified to account for the effect of surface curvature on the surface tension. The study of mixtures differs from pure fluids not only because of the surface effects but also because composition differences between the droplet and the surrounding vapor can stabilize a droplet with respect to a bulk phase.

Morrison, G.↗

Non-noble electrocatalysts for alkaline fuel cells

Carbons activated with macrocyclics have attracted increasing attention as alternative electrocatalysts for oxygen reduction. Initial activity of these catalysts is good, but performance declines rapidly. Pyrolyzing the macrocyclic on the carbon support leads to enhanced stability and the catalysts retain good activity. The approach described is designed to develop bulk doped catalysts with similar structures to pyrolyzed macrocyclic catalysts. The transition metal and coordinated ligands are dispersed throughout the bulk of the conductive carbon skeleton. Two approaches to realizing this concept are being pursued, both involving the doping of carbon precursors. In one approach, the precursor is a solid phase carbon-containing ion-exchange resin. The precursor is doped with a transition metal and/or nitrogen, and the resulting mixture is pyrolyzed. In the other approach, the precursor is a gas-phase hydrocarbon. This is introduced with a transition metal species and nitrogen species into a reactor and pyrolyzed. Several studies have been conducted to determine if there is a synergistic effect between the transition metal and nitrogen and the effect of different methods of introducing the metal-nitrogen (M-N) coordination on performance. One approach was to introduce the metal and nitrogen separately, for example, by sequentially doping FeCl3 and NH4OH into the resin. Catalysts were prepared from an undoped ion-exchange resin, a resin doped only with N, a resin doped only with Fe, and a resin doped with both Fe and N. Introduction of nitrogen alone has no beneficial effect on the performance of the catalysts. The introduction of the Fe alone significantly improves the performance in both the high and low current density regions. When both Fe and N are introduced, the performance at lower current densities (catalytic activity) is increased beyond that of the Fe-doped carbon, but the performance at higher current densities is similar to the carbon containing only Fe. Catalysts prepared from resins-Fe(bipy)3SO4 precursors have performance that is only slightly less then CoTMPP adsorbed and pyroloyzed on Vulcan XC-72. Their performance is much better than carbons which have had the N and Fe introduced separately.

Sarangapani, S.↗

Vapor Phase Catalytic Ammonia Reduction

This paper discusses the development of a Vapor Phase Catalytic Ammonia Reduction (VPCAR) teststand and the results of an experimental program designed to evaluate the potential of the technology as a water purification process. In the experimental program the technology is evaluated based upon product water purity, water recovery rate, and power consumption. The experimental work demonstrates that the technology produces high purity product water and attains high water recovery rates at a relatively high specific power consumption. The experimental program was conducted in 3 phases. In phase I an Igepon(TM) soap and water mixture was used to evaluate the performance of an innovative Wiped-Film Rotating-Disk evaporator and associated demister. In phase II a phenol-water solution was used to evaluate the performance of the high temperature catalytic oxidation reactor. In phase III a urine analog was used to evaluate the performance of the combined distillation/oxidation functions of the processor.

Flynn, Michael T.↗

Solar Selective Coatings for High Temperature Applications

Solar selective coatings are envisioned for use on minisatellites, for applications where solar energy is to be used to power heat engines or to provide thermal energy for remote regions in the interior of the spacecraft. These coatings are designed to have the combined properties of high solar absorptance and low infrared emittance. The coatings must be durable at elevated temperatures. For thermal bus applications, the temperature during operation is likely to be near 100 C. For heat engine applications. the temperature is expected to be much greater. The objective of this work was to screen candidate solar selective coatings for their high temperature durability. Candidate solar selective coatings were composed of molecular mixtures of metal and dielectric, including: nickel and aluminum oxide, titanium and aluminum oxide, and platinum and aluminum oxide. To identify high temperature durability, the solar absorptance and infrared emittance of the candidate coatings were evaluated initially, and after heating to temperatures in the range of 400 C to 700 C. The titanium and aluminum oxide molecular mixture was found to be the most durable.

Jaworske, Donald A.↗

Development of New Lunar Highland Regolith Simulant, NUW-LHT-5M

Introduction: NASA has a need for large quantities of lunar simulants that closely match future manned lunar missions at landing sites near the Lunar South Pole. The current simulant was designed to approximate NU-LHT-2M, and -4M, except using natural minerals and a fully synthetic, non-basaltic, high calcium glass. Washington Mills in Niagara Falls, NY was contracted to produce this new simulant due to their electric arc furnace (EAF) fusion technology and capabilities for crushing and sizing ceramics. The primary objectives of this work were: (1) to create a commercially produced simulant that contains a high fidelity, high calcium (An90+), low Mg/Fe glass without basaltic constituents; (2) to create a simulant that uses existing, terrestrially mined, and readily available minerals blended with a synthetic glass, and (3) accomplish objectives (1) and (2) using conventional processing methods capable of production levels that can meet substantial current and future demands of NASA projects. Another consideration was that highland simulants closest to meeting these requirements, NU-LHT-2M and -4M types, are out of production and largely out of stock. Design: The design chosen for development and production for this work is NU-LHT-2M, de-signed by Doug Stoeser and Douglas Rickman, which uses Stillwater anorthosite and norite rocks and synthetic glass. The composition targeted the average composition, glass content and particle size distribution of Apollo 16 samples [1]. The design utilizes two Stillwater minerals, anorthosite (37.7 wt.%), norite (17.6 wt.%), a commercially sourced olivine (4.7 wt.%), and a synthetic glass (40 wt.%). Processing: Stillwater rocks were hand collected and initially crushed by the USGS. Further crushing and milling was performed at Washing-ton Mills. For the glass, oxides were blended in the ap-propriate ratios, blended in a v-blender, and placed in a graphite lined, water cooled pot. The mixture was fused in Washington Mills’ pilot scale, 500 kW EAF. The molten glass was then poured into water and quenched to inhibit crystallization. Several pour/quench cycles were required to produce the total quantity of glass needed. Anorthosite, norite and olivine were milled together to the target particle size in a ball mill. The glass was ball milled separately. The complete simulant was produced by blending the milled materials. Particle size distribution, phase and chemical analyses of the materials was were per-formed at Washington Mills. Results: The glass composition was found to match the Apollo 16 oxide content average [1] quite well, with the exception of SiO2 and Fe2O3. The deviation of SiO2 and Fe2O3 from batched content was believed to be due to limitations inherent in the use of the arc furnace technique for these types of materials. A particle size distribution of the full simulant formulation closely matching the average for the Apollo 16 samples was also achieved. Fig. 1 shows the morphology of the final simulant particles. The size distribution is compared to the target in Fig. 2. Conclusions: A new lunar highlands type simulant containing a high-quality synthetic glass, closely matching an average composition of the Apollo 16 regolith was produced. Processing utilized easily scalable mineral and glass making methods.

simulant↗

Additive manufacturing of hierarchical three- dimensional micro-architected aerogels

Disclosed here is a method for making a three-dimensional micro-architected aerogel, comprising: (a) curing a reaction mixture comprising a co-sol-gel material (e.g., graphene oxide (GO)) and at least one catalyst to obtain a crosslinked co-sol-gel (e.g., GO hydrogel); (b) providing a photoresin comprising a solvent, a photoinitiator, a crosslinkable polymer precursor, and a dispersion of the crosslinked co-sol-gel (e.g., GO hydrogel); (c) curing the photoresin using projection microstereolithography layer-by-layer to produce a wet gel having a pre-designed three-dimensional structure; (d) drying the wet gel to produce a dry gel; and (e) pyrolyzing the dry gel to produce a three-dimensional micro-architected aerogel (e.g., graphene aerogel). Also disclosed is a photoresin for projection microstereolithography, comprising a solvent, a photoinitiator, a crosslinkable polymer precursor, and a dispersion of a crosslinked co-sol-gel.

Worsley, Marcus A.↗

BatteryPro: A Python Toolkit for Battery Data Analysis and Machine Learning Predictions

Analyzing battery test data for research & development can be time-consuming since battery tests often run on the order of months to years, generating large volumes of data. BatteryPro is a comprehensive Python package and software designed to facilitate advanced analysis and performance predictions for battery test data. Developed for battery researchers, it supports data types from widely used battery testing instruments, including MACCOR and Biologic cycling systems. The software provides a variety of tools for extracting and plotting key battery parameters such as time, voltage, capacity, current, and pressure. In addition to its extensive data analysis capabilities, BatteryPro features a dedicated machine learning module that employs a Bayesian Gaussian Mixture Model (GMM) to predict battery performance and degradation. Users can generate synthetic capacity fade data, calculate fade metrics, and leverage predictive models to forecast long-term battery behavior. The software's graphical user interface (GUI) enhances usability, allowing researchers to upload, merge, and analyze multiple data files with full customizability. The GUI also supports machine learning predictions, enabling users to fit models and make predictions based on selected data and parameters. BatteryPro is built using QtDesigner, scikit-learn, matplotlib, and pandas, ensuring a high level of customization, flexibility, and accuracy in battery data analysis. This tool aims to empower researchers with the ability to perform detailed battery analysis and make informed predictions, ultimately advancing the field of battery research.

25 - ENERGY STORAGE↗

An experimental investigation of the effectiveness of Ar-CO 2 shielding gas mixture for the wire arc additive process

Wire arc additive manufacturing (AM) is the process by which a large, metallic structure is built layer-by-layer using a welding arc to melt a wire feedstock. A novel opportunity exists to alter the shielding gas composition to fabricate distinct geometrical features without altering the other AM parameters. In this paper, shielding gases with varied concentrations of Argon (Ar) and CO 2 was used to deposit three distinct geometric shapes (walls, infill, and overhang) using a wire-based additive manufacturing system utilizing the gas metal arc welding (GMAW) surface tension transfer (STT) process. Computer-aided design (CAD) models were sliced with a custom-built slicer, and the sliced algorithm was converted into optimal robotic toolpaths. A custom virtual instrument (VI) was built in LabVIEW to compare the temperature profiles on the surface during each deposition process. After each deposition, the geometric features were scanned, and the surface waviness value was evaluated. Tensile and Charpy impact coupons were extracted from the wall geometries in the longitudinal and transverse directions and tested. The results indicated that a higher CO 2 content produced higher melt pool temperatures to an extent, while lower contents of CO 2 resulted in a dimensionally accurate geometry. The data also indicated that the 2%/98% CO 2 /Ar blend produced scatter in tensile strength and the analysis of variance (ANOVA) shows significant difference. However, the intermediate range of CO 2 (5–10%) resulted in uniform tensile properties. Altogether, these results indicate that a 5%/95% CO 2 /Ar blend is the ideal shielding gas for lowering process temperatures and improving mechanical properties in wire arc additive manufacturing using the gas metal arc welding surface tension transfer process. Additionally, varying concentrations of Ar/CO 2 can be used within the same part in order to modify the local properties or process parameters such as strength, toughness, temperature, or dimensional features. This may improve overall manufacturing quality without sacrificing specific properties.

42 ENGINEERING↗

Multilayered Ordered Protein Arrays Self-Assembled from a Mixed Population of Virus-like Particles

Biology shows many examples of spatially controlled assembly of cells and biomacromolecules into hierarchically organized structures, to which many of the complex biological functions are attributed. While such biological structures have inspired the design of synthetic materials, it is still a great challenge to control the spatial arrangement of individual building blocks when assembling multiple types of components into bulk materials. Here, in this study, we report self-assembly of multilayered, ordered protein arrays from mixed populations of virus-like particles (VLPs). We systematically tuned the magnitude of the surface charge of the VLPs via mutagenesis to prepare four different types of VLPs for mixing. A mixture of up to four types of VLPs selectively assembled into higher-order structures in the presence of oppositely charged dendrimers during a gradual lowering of the ionic strength of the solution. The assembly resulted in the formation of three-dimensional ordered VLP arrays with up to four distinct layers including a central core, with each layer comprising a single type of VLP. A coarse-grained computational model was developed and simulated using molecular dynamics to probe the formation of the multilayered, core-shell structure. Our findings establish a simple and versatile bottom-up strategy to synthesize multilayered, ordered materials by controlling the spatial arrangement of multiple types of nanoscale building blocks in a one-pot fabrication.

59 BASIC BIOLOGICAL SCIENCES↗

Load‐Balancing Intense Physics Calculations to Embed Regionalized High‐Resolution Cloud Resolving Models in the E3SM and CESM Climate Models

Abstract We design a new strategy to load‐balance high‐intensity sub‐grid atmospheric physics calculations restricted to a small fraction of a global climate simulation's domain. We show why the current parallel load balancing infrastructure of Community Earth System Model (CESM) and Energy Exascale Earth Model (E3SM) cannot efficiently handle this scenario at large core counts. As an example, we study an unusual configuration of the E3SM Multiscale Modeling Framework (MMF) that embeds a binary mixture of two separate cloud‐resolving model grid structures that is attractive for low cloud feedback studies. Less than a third of the planet uses high‐resolution (MMF‐HR; sub‐km horizontal grid spacing) relative to standard low‐resolution (MMF‐LR) cloud superparameterization elsewhere. To enable MMF runs with Multi‐Domain cloud resolving models (CRMs), our load balancing theory predicts the most efficient computational scale as a function of the high‐intensity work's relative overhead and its fractional coverage. The scheme successfully maximizes model throughput and minimizes model cost relative to precursor infrastructure, effectively by devoting the vast majority of the processor pool to operate on the few high‐intensity (and rate‐limiting) high‐resolution (HR) grid columns. Two examples prove the concept, showing that minor artifacts can be introduced near the HR/low‐resolution CRM grid transition boundary on idealized aquaplanets, but are minimal in operationally relevant real‐geography settings. As intended, within the high (low) resolution area, our Multi‐Domain CRM simulations exhibit cloud fraction and shortwave reflection convergent to standard baseline tests that use globally homogenous MMF‐LR and MMF‐HR. We suggest this approach can open up a range of creative multi‐resolution climate experiments without requiring unduly large allocations of computational resources.

54 ENVIRONMENTAL SCIENCES↗

Molecular dipole moment learning via rotationally equivariant derivative kernels in molecular-orbital-based machine learning

This study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) approach to modeling the contribution of electron correlation to dipole moments at the cost of Hartree–Fock computations. A MOB pairwise decomposition of the correlation part of the dipole moment is applied, and these pair dipole moments could be further regressed as a universal function of MOs. The dipole MOB features consist of the energy MOB features and their responses to electric fields. An interpretable and rotationally equivariant derivative kernel for Gaussian process regression (GPR) is introduced to learn the dipole moment more efficiently. The proposed problem setup, feature design, and ML algorithm are shown to provide highly accurate models for both dipole moments and energies on water and 14 small molecules. To demonstrate the ability of MOB-ML to function as generalized density-matrix functionals for molecular dipole moments and energies of organic molecules, we further apply the proposed MOB-ML approach to train and test the molecules from the QM9 dataset. The application of local scalable GPR with Gaussian mixture model unsupervised clustering GPR scales up MOB-ML to a large-data regime while retaining the prediction accuracy. In addition, compared with the literature results, MOB-ML provides the best test mean absolute errors of 4.21 mD and 0.045 kcal/mol for dipole moment and energy models, respectively, when training on 110 000 QM9 molecules. The excellent transferability of the resulting QM9 models is also illustrated by the accurate predictions for four different series of peptides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Techno Economic Analysis for Production of Renewable Natural Gas and Value-Added Chemicals from Forest Biomass Residues (CRADA Final Report)

West Biofuels - in collaboration with the University of California San Diego, the University of California Davis, the National Laboratory of the Rockies (NLR), the Colorado School of Mines’ Center for Hydrate Research, Placer County Air Pollution Control District, the Sierra Business Council, and the Southern California Gas Company (SoCalGas)-will demonstrate an innovative pathway to convert forest biomass to renewable gas (RG). The project, Production of Pipeline Grade Renewable Natural Gas and Value-Added Chemicals from Forest Biomass Residues, will utilize an existing pilot-scale gasification system and data and lessons learned from a lab-scale catalytic reactor design, develop, and demonstrate an integrated pilot-scale RG process with a scaled-up catalytic reactor and hydrate-based gas separation process. This robust and simple process uses a commercial proven gasifier, a commercially available catalyst that can tolerate gas contaminants, and a gas separation process that simplifies the downstream processing. Current testing has shown that the process can yield a large amount of methane rich renewable gas in addition to a mixture of propanol, ethanol and other higher alcohols and the relative amounts can be controlled by shifting the process conditions. This process is novel and groundbreaking because the product mixture of RG and valuable alcohols byproducts makes RG production economically feasible at $\$$12 per million British thermal units (MMBtu) or less using forest biomass from high hazard zones.

09 BIOMASS FUELS↗

EPS (Electric Particulate Suspension) Microgravity Technology Provides NASA with New Tools

The Electric Particulate Suspension is a fire safety ignition test system being developed at Iowa State University with NASA support for evaluating combustion properties of powders, powder-gas mixtures, and pure gases in microgravity and gravitational atmospheres (quenching distance, ignition energy, flammability limits). A separate application is the use of EPS technology to control heat transfer in vacuum and space environment enclosures. In combustion testing, ignitable powders (aluminum, magnesium) are introduced in the EPS test cell and ignited by spark, while the addition of inert particles act as quenching media. As a combustion research tool, the EPS method has potential as a benchmark design for quenching powder flames that would provide NASA with a new fire safety standard for powder ignition testing. The EPS method also supports combustion modeling by providing accurate measurement of flame-quenching distance as an important parameter in laminar flame theory since it is closely related to characteristic flame thickness and flame structure. In heat transfer applications, inert powder suspensions (copper, steel) driven by electric fields regulate heat flow between adjacent surfaces enclosures both in vacuum (or gas) and microgravity. This simple E-field control can be particularly useful in space environments where physical separation is a requirement between heat exchange surfaces.

Colver, Gerald M.↗

NASA Tech Briefs, March 2013

Topics covered include: Remote Data Access with IDL Data Compression Algorithm Architecture for Large Depth-of-Field Particle Image Velocimeters Vectorized Rebinning Algorithm for Fast Data Down-Sampling Display Provides Pilots with Real-Time Sonic-Boom Information Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery Monitoring and Acquisition Real-time System (MARS) Analog Signal Correlating Using an Analog-Based Signal Conditioning Front End Micro-Textured Black Silicon Wick for Silicon Heat Pipe Array Robust Multivariable Optimization and Performance Simulation for ASIC Design; Castable Amorphous Metal Mirrors and Mirror Assemblies; Sandwich Core Heat-Pipe Radiator for Power and Propulsion Systems; Apparatus for Pumping a Fluid; Cobra Fiber-Optic Positioner Upgrade; Improved Wide Operating Temperature Range of Li-Ion Cells; Non-Toxic, Non-Flammable, -80 C Phase Change Materials; Soft-Bake Purification of SWCNTs Produced by Pulsed Laser Vaporization; Improved Cell Culture Method for Growing Contracting Skeletal Muscle Models; Hand-Based Biometric Analysis; The Next Generation of Cold Immersion Dry Suit Design Evolution for Hypothermia Prevention; Integrated Lunar Information Architecture for Decision Support Version 3.0 (ILIADS 3.0); Relay Forward-Link File Management Services (MaROS Phase 2); Two Mechanisms to Avoid Control Conflicts Resulting from Uncoordinated Intent; XTCE GOVSAT Tool Suite 1.0; Determining Temperature Differential to Prevent Hardware Cross-Contamination in a Vacuum Chamber; SequenceL: Automated Parallel Algorithms Derived from CSP-NT Computational Laws; Remote Data Exploration with the Interactive Data Language (IDL); Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals; Partitioned-Interval Quantum Optical Communications Receiver; and Practical UAV Optical Sensor Bench with Minimal Adjustability.

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