Search NASA⌕ Search

SEARCH · Search NASA

Results for “DPS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

Development of a High-Propellant Throughput Small Spacecraft Electric Propulsion System to Enable Lower Cost NASA Science Missions

This paper describes recent progress at the NASA Glenn Research Center (GRC) in the development and demonstration of an integrated high-propellant throughput small spacecraft electric propulsion (HT-SSEP) system based on a Hall-effect thruster. A center-mounted cathode and an innovative magnetic circuit topology were implemented in the design of the Hall-effect thruster to achieve high-propellant throughput, high performance, and efficient packaging. To minimize technical risk, the HT-SSEP development approach sought to limit design features and materials to those with a clear path-to-flight. A propellant throughput capability of greater than 100 kg at a minimum thruster efficiency of 50% was targeted. The proof-of-concept NASA-H64M laboratory model (LM) thruster was designed, fabricated, and tested at GRC in fiscal year 2018. The thruster development leveraged heritage Hall-effect thruster design and manufacturing processes wherever appropriate. Recent NASA advances in Hall-effect thruster technology were also leveraged. A scalable discharge power supply (DPS) capable of powering the H64M-LM was developed, then demonstrated as part of an integrated system test. The DPS uses commercial off-the-shelf components with spaceflight equivalents. A keeper supply with DC ignitor was breadboarded, then demonstrated with a laboratory cathode. Finally, feed system trade studies were performed to ascertain what feed system architecture might be appropriate for an HT-SSEP system. This paper details the motivations for the project, the development approach, the chosen sub-system architectures, design considerations, and test results.

Benavides, Gabriel F.↗

Biomass Harmonization and SAR Analysis with the Multi-mission Algorithm and Analysis Platform (MAAP)

The Multi‐mission Algorithm and Analysis Platform (MAAP) is a collaborative effort between NASA and the European Space Agency (ESA) to support above ground biomass (AGB) research in an open science framework. MAAP brings together relevant data, algorithms, and computing capabilities in a common cloud environment to address the challenges of sharing and processing data from field, airborne and satellite measurements. MAAP was publicly released in October 2021, providing computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of data. MAAP has allowed scientists from both North America and Europe to collaborate on the generation and analysis/visualization of data derived from multiple, discipline-adjacent missions in an open, collaborative environment that has reached beyond traditional scientific investigation. MAAP has been used to support multiple scientific activities. To date, existing LiDAR data from multiple platforms has been calibrated with field measurements and combined for more comprehensive and accurate estimates of above ground biomass AGB; these LiDAR platforms include airborne (e.g. LVIS), the International Space Station (NASA’s Global Ecosystem Dynamics Investigation (GEDI), and satellites (e.g. ICESat-2). The current challenge is to effectively and seamlessly combine the aforementioned LiDAR-based data with new data sources such as P-band RADAR from ESA’s upcoming BIOMASS mission, existing ESA Sentinel-1 C-band SAR, and the 30 PB/yr of high cadence global coverage L-band SAR data from the upcoming NASA-ISRO SAR (NISAR) mission. Recent analysis using MAAP merged ICESat-2 and optical data (Harmonized Landsat Sentinel) produced the most comprehensively precise estimate of boreal-wide AGB to date. Another effort using MAAP is the production and open distribution of global comparisons of AGB map estimates, including from ICESat-2 and GEDI, to bolster stakeholder uptake for policy applications. These map estimates will feed into the Intergovernmental Panel on Climate Change (IPCC) database, likely aiding the next Global Carbon Stocktake of the UNFCCC. Furthermore, the biomass retrieval intercomparison exercise BRIX-2 could benefit from the MAAP providing standardized test cases (based on airborne campaign and spaceborne data) allowing the community to develop and apply retrieval algorithms based on these test cases, while forthcoming SAR data training curricula could also use the MAAP as a teaching and learning platform. The MAAP is meeting the challenges inherent in international, open science collaboration and large scale computing with a platform that is entirely open source and cloud native, using open standards for data access, manipulation, protocols, and formats. The MAAP data system consists of a dedicated data store whose data is indexed in an online catalog conforming to established metadata, application programmatic interfaces (APIs), and service interface standards, using an implementation of the open sourced NASA Common Metadata Repository. Federation of user identities allows users from either NASA or ESA to access and consume services from the other using a unified metadata catalog for the data utilized across the ESA and NASA MAAP platforms. Similarly, we are exploring how to increase interoperability to achieve a common approach to packaging, orchestrating and executing algorithms, with interoperable access to data for subsetting, fast browse, and cloud-optimized access, all using interoperable standards such as those from the Open Geospatial Consortium (OGC). Designed for interoperability, ESA and NASA utilize a common architecture for the software platform. It provides a cloud-based algorithm development environment (ADE) that enables scientists to develop algorithms collaboratively with access to the MAAP data catalog as well as other data archives. MAAP provides an Eclipse Che-based ADE supporting both Python and R languages, popular in this biomass community. Algorithms developed and containerized within the ADE can be deployed to run to thousands of computational nodes in the MAAP’s data processing system (DPS), dramatically speeding up processing and giving scientists a rapid, iterative turnaround of results. NASA’s implementation of the DPS is based on the Hybrid Science Data System (HySDS) framework, used by NASA flight projects to produce Earth science standard products.

cloud computing↗

Gold‐Catalyzed C−H Functionalization Polycondensation for the Synthesis of Aromatic Polymers

Abstract Homogeneous gold (Au) complexes have demonstrated tremendous utility in modern organic chemistry; however, their application for the synthesis of polymers remains rare. Herein, we demonstrate the first catalytic application of Au complexes toward the polycondensation of alkyne‐containing comonomers and heteroarene nucleophiles. Polymerization occurs through successive intermolecular hydroarylation reactions to produce high molecular weight aromatic copolymers with 1,1‐disubstituted alkene backbone linkages. Clear correlations between the rate and degree of polymerization (DP) were established based on catalyst structure and counterion pairing, thus enabling polymerization reactions that proceeded with remarkable efficiency, high reactivity, and exceptional DPs. The reactivity is broad in scope, enabling the copolymerization of highly functionalized aromatic and aliphatic monomers. These results highlight the untapped utility of Au catalysis in providing access to new macromolecular constructs.

King, Eric R.↗

Gold–Catalyzed C–H Functionalization Polycondensation for the Synthesis of Aromatic Polymers

Homogeneous gold (Au) complexes have demonstrated tremendous utility in modern organic chemistry; however, their application for the synthesis of polymers remains rare. Herein, we demonstrate the first catalytic application of Au complexes toward the polycondensation of alkyne-containing comonomers and heteroarene nucleophiles. Polymerization occurs through successive intermolecular hydroarylation reactions to produce high molecular weight aromatic copolymers with 1,1-disubstituted alkene backbone linkages. Clear correlations between the rate and degree of polymerization (DP) were established based on catalyst structure and counterion pairing, thus enabling polymerization reactions that proceeded with remarkable efficiency, high reactivity, and exceptional DPs. The reactivity is broad in scope, enabling the copolymerization of highly functionalized aromatic and aliphatic monomers. Furthermore, these results highlight the untapped utility of Au catalysis in providing access to new macromolecular constructs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-modal characterization of the B2 phase in the Ta-Re binary system

The energy and transportation industries demand materials that retain their mechanical property at high temperatures. Refractory complex concentrated alloys (RCCAs) with a BCC + B2 microstructure offer a potential solution, where maintaining the high temperature mechanical properties can be achieved by precipitation strengthening. This depends on the B2 phase in RCCAs being thermodynamically stable with a high solvus temperature. Recently, we predicted the high temperature stability of the B2 structure in the Ta-Re binary system, using density functional theory. Here, in this study, we provide experimental evidence for the existence of this phase for the first time, using a Ta 65 Re 35 alloy. Despite Ta-Re binary phase diagrams predicting a single-phase BCC microstructure for Ta 65 Re 35 , we show that a high Z nanoscale secondary phase appears after heat treatment at 1550 °C and 1100 °C. Scanning transmission electron microscopy (STEM) revealed that this phase has a cubic structure and is equiatomic TaRe though B2 superlattice reflections were absent in fast Fourier transforms (FFT) and diffraction patterns (DPs). DP simulations indicate that the B2 TaRe superlattice reflections are up to two orders of magnitude weaker than their fundamental reflections, making their detection challenging via electron microscopy. Neutron diffraction confirmed the second phase had a B2 structure. This study identified a previously unobserved high temperature stable B2 phase in the Ta-Re system, enabling the development of new high temperature BCC + B2 RCCAs.

36 MATERIALS SCIENCE↗

Robust bidding strategy for aggregation of distributed prosumers in flexiramp market

Distributed prosumers (DPs) are the grid customers that own energy production/storage assets. Due to the flexibility and fast response of their assets, they can procure ancillary service products (ASP) in the wholesale market. An appealing ASP offered by California ISO in the real-time market (RTM) is flexiramp for which market participants do not submit direct offers, and the compensation is based on their energy opportunity costs. Here in this report, we propose a bidding strategy model for DP aggregator participation in the RTM considering energy and flexiramp. First, we develop a risk-averse optimization to determine the optimal energy and reserve product to trade in day-ahead market while considering proper amounts of flexiramp to trade in the RTM. In the RTM, to obtain optimal amounts of energy and flexiramp, the aggregator must submit hourly multi-level price-quantity energy bids for multiple RTM intervals with 15 min time-steps. On this basis, we propose a robust hourly economic bidding strategy model that determines the optimal energy bids in the RTM. We develop an adjustable robust counterpart of the model to address the RTM energy and flexiramp price uncertainties. The simulation results justify the efficacy of our proposed framework in gaining profits from the wholesale market.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Correlated 4D-STEM and EDS for the classification of fine Beta-precipitates in aluminum alloy AA 6063-T6

Tuning the properties of aluminum alloys AA 6063-T6 involves artificial aging to induce precipitate formation, particularly β’’ and β’ phases. Previous characterization challenges due to their similar appearance are addressed here by correlating 4D scanning transmission electron microscopy (4DSTEM) and energy-dispersive spectroscopy (EDS) mapping. This approach allows us to analyze the structure and composition of precipitates individually, overcoming limitations of conventional imaging and structural analysis techniques when the precipitates appear simultaneously, as is often the case. We present detailed characterizations of needle-shaped Beta precipitates, revealing distinct diffraction patterns (DPs) and compositional differences. The method's applicability extends beyond aluminum alloys, offering a promising strategy for complex composite material characterization with multimodal scanning transmission electron microscopy (STEM) techniques.

36 MATERIALS SCIENCE↗

Taste Perception of Branched Maltooligosaccharides

Oral processing of starch generates linear and branched maltooligosaccharides (MOS). This study investigates the impact of branching and the degree of polymerization (DP) on MOS taste detection. Three branched MOS samples (A−C) were enzymatically prepared from gelatinized waxy corn starch and characterized using reducing-end assays, MALDI-TOF MS, β-amylase hydrolysis, and GC-MS linkage analysis. Samples A, B, and C had average DPs of 6, 10, and 18, respectively, with α-1,6 branch points comprising 9−13% of glycosidic bonds; linear MOS were negligible. In triangle tests, participants evaluated MOS samples and a maltose control at 75 mM, with and without lactisole, a sweet receptor inhibitor. All samples were detectable without lactisole (d′ = 1.81−2.9; p < 0.05), but not with lactisole (d′ = 0−0.61; p > 0.05). These findings demonstrate that α-1,6 branching enables MOS detection via the sweet receptor, not the putative “starchy” receptor, underscoring the importance of glycosidic structure in carbohydrate taste perception.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bottlebrush Block Copolymer Thin Films

The self-assembly of block copolymers (BCPs) in thin films is governed by interfacial interactions (enthalpy) between the blocks and interfaces (at both the substrate and the surface). Advantage can also be taken of entropy to control the polymer orientation. Here, we synthesized a series of bottlebrush block copolymers (BBCPs), with deuterated polystyrene (DPS) as the core block and poly­(solketal acrylate) (PSA) as the corona block, where the backbone length (N BB) and grafting densities (GDs) were varied. The hydrophobic PSA block was converted to a hydrophilic poly­(glyceryl acrylate) (PGA) block by solid-state hydrolysis, bringing the BBCP from a disordered state into an ordered state with a lamellar microdomain morphology. The orientation of the morphology as a function of distance from the interfaces was systematically investigated by atomic force microscopy (AFM), interference microscopy, grazing-incidence small-angle X-ray scattering (GISAXS), and grazing-incidence small angle neutron scattering (GISANS). For N BB = 1 (diblock BCP), a mixed lamellar orientation was found. For N BB = 5 (star-like BBCP), a vertical orientation of the lamellar microdomains was found dominantly at the interfaces that propagated into the bulk of the film due to the entropic penalty associated with constraints on the junction points. Increasing the N BB to 50 (rod-like BBCP) and 100 (worm-like BBCP) yielded a random orientation, as the side chains became overcrowded when aligned in the same direction. By reducing the grafting density (GD) of a N BB = 50 BBCP from 100% to 75% and 50% by the incorporation of spacers into the backbone, the steric hindrance of side chains is reduced markedly, facilitating a vertical orientation of the lamellar microdomains. However, the vertical orientation becomes more random within the bulk of the thin film for different BBCP architectures. By modifying the substrate with a layer of PS, the preferential interactions between the core block of the BBCP and the interfaces induce a reconfiguration of the BBCP, drawing the core block out to contact substrate directly driven by enthalpy. Under these conditions, N BB = 5 showed a predominantly parallel orientation of the lamellar microdomains with the corona block minimizing contact with the substrate. Higher N BB values of 50 and 100 showed a more random orientation of the lamellar microdomains at different depths on the PS-modified substrate. Overall, thin-film morphology was regulated by tuning the configuration of the BBCP, varying the entropic contribution to the microdomain orientation.

Chen, Zhan↗

Modeling the aqueous interface of amorphous TiO 2 using deep potential molecular dynamics

Amorphous titanium dioxide (a-TiO 2 ) is widely used as a coating material in applications such as electrochemistry and self-cleaning surfaces where its interface with water has a central role. However, little is known about the structures of the a-TiO 2 surface and aqueous interface, particularly at the microscopic level. In this work, we construct a model of the a-TiO 2 surface via a cut-melt-and-quench procedure based on molecular dynamics simulations with deep neural network potentials (DPs) trained on density functional theory data. After interfacing the a-TiO 2 surface with water, we investigate the structure and dynamics of the resulting system using a combination of DP-based molecular dynamics (DPMD) and ab initio molecular dynamics (AIMD) simulations. Both AIMD and DPMD simulations reveal that the distribution of water on the a-TiO 2 surface lacks distinct layers normally found at the aqueous interface of crystalline TiO 2 , leading to an ~10 times faster diffusion of water at the interface. Bridging hydroxyls (Ti 2 –O b H) resulting from water dissociation decay several times more slowly than terminal hydroxyls (Ti–O w H) due to fast Ti–O w H 2 → Ti–O w H proton exchange events. These results provide a basis for a detailed understanding of the properties of a-TiO 2 in electrochemical environments. Moreover, the procedure of generating the a-TiO 2 -interface employed here is generally applicable to studying the aqueous interfaces of amorphous metal oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Magnetic ground state of La 2 LiMoO 6 : A comparison with other Mo 5+ ( S=1/2 ) double perovskites

La 2 LiMoO 6 is a double perovskite (DP) with P2 1 /n symmetry based on the Mo5+ ion, 4d1, t2g1, S=1/2. It is isostructural with Sr 2 YMoO 6 , the magnetic ground state of which is apparently a very unusual collective spin singlet or valence-bond glass state as is the case for cubic (Fm-3m) Ba 2 YMoO 6 . Initial studies of La 2 LiMoO 6 suggested a different ground state from the other DPs but no clear conclusions could be drawn. A more detailed study is presented here including magnetic susceptibility, heat capacity, and elastic neutron-scattering results. This DP is now well characterized as an antiferromagnet, T N =18K, via observation of magnetic Bragg peaks in neutron scattering and an anomaly in the magnetic heat capacity. The ordering wave vector is k=( 1/21/2 0), consistent with a type I face-centered-cubic magnetic structure, and the ordered moment on Mo 5+ is 0.32(11)μ B , much reduced from the spin-only value of 1μ B . The index, f=|v c |/T N ~3, indicates a low level of frustration. The heat-capacity data above T N can be interpreted in terms of a one-dimensional spin-correlation model, as can the low-temperature data which follow a T 1 power law. This is consistent with an earlier suggestion. The difference with isostructural Sr 2 YMoO 6 is attributed to differences in the local distortion of the Mo–O octahedron and the resulting orbital ordering.

36 MATERIALS SCIENCE↗

Development and transferability of neural-network models for plasma-surface interactions

Plasma-surface interactions are increasingly critical to modern technologies; yet, accurate molecular dynamics simulations remain limited by the capabilities of interatomic potentials. Deep Potentials (DPs) promise to revolutionize the field by providing a systematic method for producing accurate interatomic potentials. The primary challenge of DP development is selecting a dataset, which efficiently spans the set of atomic environments one expects to encounter in the subsequent molecular dynamics simulations. The computational cost of density functional theory calculations, which are the typical basis for DP development, makes it impossible to directly verify the quality of a given DP. To address this challenge, we explore the development of a deep-learned interatomic potential, “DeepREBO,” trained to reproduce the behavior of the REBO2 empirical potential, enabling direct validation of training methodology and transferability. Using an active learning framework, we begin with a minimal dataset and iteratively expand it to train a Deep Potential-Smooth Edition model that faithfully reproduces REBO2 results for 25 eV hydrogen bombardment of diamond (001), a particularly challenging case. We show that small, carefully curated datasets can outperform large, unguided ones, with effective models requiring fewer than 15 000 snapshots. Subsequent transferability tests demonstrate that while DeepREBO generalizes well to diamond (111) surfaces, performance degrades for amorphous carbon or higher-energy impacts, highlighting the need for use-case-specific training data. We also evaluate methods to improve short-range repulsion. This study outlines best practices for training robust deep potentials and underscores the importance of dataset design for predictive plasma simulations.

Ab-initio molecular dynamics↗

Arroyo Mocho Habitat Suitability Assessment for Sensitive Reptiles, Amphibians, and Fish

Sequoia Ecological Consulting, Inc. (Sequoia) has prepared this habitat suitability assessment for the purpose of assessing current habitat suitability and evaluating the potential presence of special-status species at and near the Arroyo Mocho Pumping Station (Arroyo Mocho). The Study Area is located 7.5 miles southeast of the City of Livermore in Alameda County, California. Our analysis provides a description of presence and habitat suitability for special-status reptiles, amphibians, and fish within the Study Area and identifies potential conservation measures. Special-status animals are designated by the US Fish and Wildlife Service (USFWS) and the California Department of Fish and Wildlife (CDFW). This analysis focuses on California tiger salamander (Ambystoma californiense), California red-legged frog (Rana draytonii), foothill yellow-legged frog (Rana boylii), western pond turtle (Emys marmorata), Alameda whipsnake (Masticophis lateralis euryxanthus), Coast horned lizard (Phrynosoma blainvilli), and central California coast distinct population segment (DPS) steelhead (Oncorhynchus mykiss), per the request of Lawrence Livermore National Laboratory.

54 ENVIRONMENTAL SCIENCES↗

Stochastic Approaches for Calculating and Aggregating Detection Probabilities for Nuclear Material Diversion

The authors built and tested a stochastic simulation to estimate achieved detection probabilities (DPs) on a stratum basis, over a tailorable range of diverted amounts from 0 to 2 significant quantities (SQ), using typical International Atomic Energy Agency (IAEA) inspection data: i.e., SQ in stratum, number of items, number of gross/partial/bias defect measurements conducted, and realistic relative standard deviation (RSD) values for typical IAEA verification measurements. For bulk strata, the model calculates achieved DP at 0.01 SQ diversion increments; for item strata, the model calculates DP using the smallest realistic diversion increment (e.g., a plate, pin, or coupon). After successfully benchmarking against IAEA deterministic models, the simulation was used to test the sensitivity of DP to certain standard assumptions and selected input parameters. First, the equal defect assumption was tested; the results suggest significant complexity in the effectiveness of partial defect measurements. Next, the authors explored the sensitivity of DP to the assumed RSD of attribute tests. Then, the authors compared non-normal models for instrument performance (e.g., logistic, step, or arbitrary functions) to the typical results from a normal distribution (characterized by RSD). This last comparison was supplemented with experimentally derived performance data for an HM-5 gamma spectrometer. The HM-5 was used to make enrichment measurements on both LEU and HEU MTR fuel elements as plates were removed, and the results fit with logistic and step curves and applied in the simulation. These stochastic DP results were compared to DP estimates from a deterministic model assuming a normal curve and typical RSD, yielding insights that could improve effectiveness in the field. These early results illustrate the potential of stochastic models to better understand achieved DP and to improve safeguards effectiveness.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Impact of Increased Latent Generations on Sensitivity Calculations with SCALE [Slides]

Depending on the system, energy, and/or nuclide, altering the number of latent generations can significantly impact generated sensitivity coefficients. In general, as the number of latent generations increases, the accuracy of the generated sensitivity value compared with the DP value increases and there is a significant increase in the uncertainty with generated sensitivity values. IFP generated sensitivities appear to be more stable than those with CLUTCH. Complex systems, even with IFP and increased latent generations can still produce poor results (i.e., MPC- 32). This reiterates the importance of performing DPs to confirm sensitivities. IFP-Shift and CLUTCH can take advantage of parallel computing abilities. Work continues in this area as additional parameters and calculational methods are examined to provide analysts insights to successfully generating sensitivity coefficients for confirmatory analyses and validation efforts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

SRF cavities and Superconducting qubits for Gravitational Waves and Dark Photons detection

The report is a short review which focuses on the employment of a Superconducting Radio Frequency (SRF) cavity for detection of Gravitational Waves (GWs). This first part is inspired by the works of Berlin’s group. In the second part, we analyze also the idea to use a cavity-qubit system for the GWs detection and the Dark Photons (DPs) detection. In this case, the starting point is the work of Dixit’s group which will be extended for SQMS cavities.

43 PARTICLE ACCELERATORS↗

Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators

The control of high-dimensional distributed parameter systems (DPS) remains a challenge when explicit coarse-grained equations are unavailable. Classical equation-free (EF) approaches rely on fine-scale simulators treated as black-box timesteppers. However, repeated simulations for steady-state computation, linearization, and control design are often computationally prohibitive, or the microscopic timestepper may not even be available, leaving us with data as the only resource. We propose a data-driven alternative that uses local neural operators, trained on spatiotemporal microscopic/mesoscopic data, to obtain efficient short-time solution operators. These surrogates are employed within Krylov subspace methods to compute coarse steady and unsteady-states, while also providing Jacobian information in a matrix-free manner. Krylov-Arnoldi iterations then approximate the dominant eigenspectrum, yielding reduced models that capture the open-loop slow dynamics without explicit Jacobian assembly. Both discrete-time Linear Quadratic Regulator (dLQR) and pole-placement (PP) controllers are based on this reduced system and lifted back to the full nonlinear dynamics, thereby closing the feedback loop.

93B52, 93C20, 47N70, 65J15, 65M32, 68T07, 68T20, 6↗