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Results for “Vector Potential”

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 1,063 records · Page 59

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NASA NTRS1986

Delta-configurations - Flare activity and magnetic-field structure

Complex sunspots in four active regions of April and May 1980, all exhibiting regions of magnetic classification delta, were studied using data from the NASA Marshall Space Flight Center vector magnetograph. The vector magnetic field structure in the vicinity of each delta was determined, and the location of the deltas in each active region was correlated with the locations and types of flare activity for the regions. Two types of delta-configuration were found to exist, active and inactive, as defined by the relationships between magnetic field structure and activity. The active delta exhibited high flare activity, strong horizontal gradients of the longitudinal (line-of-sight) magnetic field component, a strong transverse (perpendicular to line-of-sight) component, and a highly nonpotential orientation of the photospheric magnetic field, all indications of a highly sheared magnetic field. The inactive delta, on the other hand, exhibited little or no flare production, weaker horizontal gradients of the longitudinal component, weaker transverse components, and a nearly potential, nonsheared orientation of the magnetic field. It is concluded that the presence of such sheared fields is the primary signature by which the active delta may be distinguished, and that it is this shear which produces the flare activity of the active delta.

Patty, S. R.↗

NASA NTRS2017

Estrous Cyclicity in Mice During Simulated Weightlessness

Hindlimb unloading (HU) is a rodent model system used to simulate weightlessness experienced in space. However, some effects of this approach on rodent physiology are under-studied, specifically the effects on ovarian estrogen production which drives the estrous cycle. To resolve this deficiency, we conducted a ground-based validation study using the HU model, while monitoring estrous cycles in 16-weeks-old female C57BL6 mice. Animals were exposed to HU for 12 days following a 3 day HU cage acclimation period, and estrous cycling was analyzed in HU animals (n=22), normally loaded HU Cage Pair-Fed controls (CPF; n=22), and Vivarium controls fed ad libitum (VIV; n=10). Pair feeding was used to control for potential nutritional deficits on ovarian function. Vaginal cells were sampled daily in all mice via saline lavage. Cells were dried and stained with crystal violet, and the smears evaluated using established vaginal cytology techniques by two individuals blinded to the animal treatment group. Estrous cyclicity was disrupted in nearly all HU and CPF mice, while those maintained in VIV had an average normal cycle length of 4.8+/- 0.5 days, with all stages in the cycle visibly observed. CPF and HU animals arrested in the diestrous phase, which precedes the pre-ovulatory estrogen surge. Additionally, infection-like symptoms characterized by vaginal discharge and swelling arose in several HU animals, which we suspect was due to an inability of these mice to properly groom themselves, and/or due to the change in the gravity vector relative to the vaginal opening, which prevented drainage of the lavage solution. Pair-feeding resulted in similar weight gains of HU and CPF (1.5% vs 3.0%, respectively). The current results indicate that pair-feeding controlled weight gain and that the HU cage alone influenced estrous cyclicity. Thus, longer acclimation needs to be tested to determine if and when normal estrous cycling resumes in non-loaded mice in HU cages prior to HU testing. Future studies might also examine whether modifications to the vaginal lavage procedure might prevent the onset of the infection-like symptoms, and allow estrous cyclicity to be measured in this model system. Research supported by NNX15AB48G to JST.

Hindlimb Unloading↗

NASA NTRS2017

Estrous Cyclicity of Mice During Simulated Weightlessness

Hindlimb unloading (HU) is a rodent model system used to simulate weightlessness experienced in space. However, some effects of this approach on rodent physiology are under-studied, specifically the effects on ovarian estrogen production which drives the estrous cycle. To resolve this deficiency, we conducted a ground-based validation study using the HU model, while monitoring estrous cycles in 16-weeks-old female C57BL6 mice. Animals were exposed to HU for 12 days following a 3 day HU cage acclimation period, and estrous cycling was analyzed in HU animals (n22), normally loaded HU Cage Pair-Fed controls (CPF; n22), and Vivarium controls fed ad libitum (VIV; n10). Pair feeding was used to control for potential nutritional deficits on ovarian function. Vaginal cells were sampled daily in all mice via saline lavage. Cells were dried and stained with crystal violet, and the smears evaluated using established vaginal cytology techniques by two individuals blinded to the animal treatment group. Estrous cyclicity was disrupted in nearly all HU and CPF mice, while those maintained in VIV had an average normal cycle length of 4.8 0.5 days, with all stages in the cycle visibly observed. CPF and HU animals arrested in the diestrous phase, which precedes the pre-ovulatory estrogen surge. Additionally, infection-like symptoms characterized by vaginal discharge and swelling arose in several HU animals, which we suspect was due to an inability of these mice to properly groom themselves, andor due to the change in the gravity vector relative to the vaginal opening, which prevented drainage of the lavage solution. Pair-feeding resulted in similar weight gains of HU and CPF (1.5 vs 3.0, respectively). The current results indicate that pair-feeding controlled weight gain and that the HU cage alone influenced estrous cyclicity. Thus, longer acclimation needs to be tested to determine if and when normal estrous cycling resumes in non-loaded mice in HU cages prior to HU testing. Future studies might also examine whether modifications to the vaginal lavage procedure might prevent the onset of the infection-like symptoms, and allow estrous cyclicity to be measured in this model system.

fertilit↗

DOE OSTI2023

Machine learning assisted phase and size-controlled synthesis of iron oxide particles

Synthesis of iron oxides with specific phases and particle sizes is a crucial challenge in various fields, including materials science, energy storage, biomedical applications, environmental science, and earth science. However, despite significant advances in this area, much of the current palette of particle outcomes has been based on time-consuming trial-and-error exploration of synthesis conditions. The present study was designed to explore a very different approach to 1) predict the outcome of synthesis from specified reaction parameters based on using machine learning (ML) techniques, and 2) correlate sets of parameters to obtain products with desired outcomes by a newly designed recommendation algorithm. To achieve this, four ML algorithms were tested, namely random forest, logistic regression, support vector machine, and k-nearest neighbor. Among the models, random forest outperformed the others, attaining 96% and 81% accuracy when predicting the phase and size of iron oxide particles in the test dataset. Surprisingly, the permutation feature importance analysis revealed that volume, which may strongly relate to pressure, was one of the important features, along with precursor concentration, pH, temperature, and time, influencing the phase and size of iron oxide particles during synthesis. To verify the robustness of the random forest models, prediction and experimental results were compared based on 24 randomly generated methods in additive and non-additive systems not included in the datasets. The predictions of product phase and particle size from the models agreed well with the experimental results. Furthermore, a searching and ranking algorithm was developed to recommend potential synthesis parameters for obtaining iron oxide products with the desired phase and particle size from previous studies in the dataset. Furthermore, this study lays the foundation for a closed-loop approach in materials synthesis and preparation, beginning with suggesting potential reaction parameters from the dataset and predicting potential outcomes, followed by conducting experiments and analyses, and ultimately enriching the dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Validating the galaxy and quasar catalog-level blinding scheme for the DESI 2024 analysis

In the era of precision cosmology, ensuring the integrity of data analysis through blinding techniques is paramount — a challenge particularly relevant for the Dark Energy Spectroscopic Instrument (DESI). DESI represents a monumental effort to map the cosmic web, with the goal to measure the redshifts of tens of millions of galaxies and quasars. Given the data volume and the impact of the findings, the potential for confirmation bias poses a significant challenge. To address this, we implement and validate a comprehensive blind analysis strategy for DESI Data Release 1 (DR1), tailored to the specific observables DESI is most sensitive to: Baryonic Acoustic Oscillations (BAO), Redshift-Space Distortion (RSD) and primordial non-Gaussianities (PNG). We carry out the blinding at the catalog level, implementing shifts in the redshifts of the observed galaxies to blind for BAO and RSD signals and weights to blind for PNG through a scale-dependent bias. We validate the blinding technique on mocks as well as on data by applying a second blinding layer to perform a series of sanity checks; the latter allows probing complexities in real data not captured in mocks. We find that the blinding strategy alters the data vector in a controlled way, and the BAO and RSD analysis choices are robust to blinding. The successful validation of the blinding strategy paves the way for the unblinded DESI DR1 analysis, alongside future blind analyses with DESI and other surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1989

Accurate quantum chemical calculations

An important goal of quantum chemical calculations is to provide an understanding of chemical bonding and molecular electronic structure. A second goal, the prediction of energy differences to chemical accuracy, has been much harder to attain. First, the computational resources required to achieve such accuracy are very large, and second, it is not straightforward to demonstrate that an apparently accurate result, in terms of agreement with experiment, does not result from a cancellation of errors. Recent advances in electronic structure methodology, coupled with the power of vector supercomputers, have made it possible to solve a number of electronic structure problems exactly using the full configuration interaction (FCI) method within a subspace of the complete Hilbert space. These exact results can be used to benchmark approximate techniques that are applicable to a wider range of chemical and physical problems. The methodology of many-electron quantum chemistry is reviewed. Methods are considered in detail for performing FCI calculations. The application of FCI methods to several three-electron problems in molecular physics are discussed. A number of benchmark applications of FCI wave functions are described. Atomic basis sets and the development of improved methods for handling very large basis sets are discussed: these are then applied to a number of chemical and spectroscopic problems; to transition metals; and to problems involving potential energy surfaces. Although the experiences described give considerable grounds for optimism about the general ability to perform accurate calculations, there are several problems that have proved less tractable, at least with current computer resources, and these and possible solutions are discussed.

Bauschlicher, Charles W., Jr.↗

NASA NTRS1994

Equilibrium and Dynamics Properties of Poly(oxyethylene) Melts and Related Poly(alkylethers) from Simulations and Ab Initio Calculations

Molecular dynamics simulations of POE melts have been performed utilizing a potential force field parameterized to reproduce conformer energies and rotational energy barriers in dimethoxyethane as determined from ab initio electronic structure calculations. Chain conformations and dimensions of POE from the simulations were found to be in good agreement with predictions of a rotational isomeric state (RIS) model based upon the ab initio conformational. energies. The melt chains were found to be somewhat extended relative to chains at theta conditions. This effect will be discussed in light of neutron scattering experiments which indicate that POE chains are extended in the melt relative to theta solutions. The conformational characteristics of POE chains will also be compared with those of other poly (alkylethers), namely poly(oxymethylene), poly(oxytrimethylene) and poly(oxytetramethylene). Local conformational dynamics were found to be more rapid than in polymethylene. Calculated C-H vector correlation times were found to be in reasonable agreement with experimental values from C-13 NMR spin-lattice relaxation times. The influence of ionic salts on local conformations and dynamics will also be discussed.

Smith, Grant D.↗

DOE OSTI2020

Aedes aegypti Odorant Binding Protein 22 selectively binds fatty acids through a conformational change in its C-terminal tail

Aedes aegypti is the primary vector for transmission of Dengue, Zika and chikungunya viruses. Previously it was shown that Dengue virus infection of the mosquito led to an in increased expression of the odorant binding protein 22 (AeOBP22) within the mosquito salivary gland and that siRNA mediated knockdown of AeOBP22 led to reduced mosquito feeding behaviors. Insect OBPs are implicated in the perception, storage and transport of chemosensory signaling molecules including air-borne odorants and pheromones. AeOBP22 is unusual as it is additionally expressed in multiple tissues, including the antenna, the male reproductive glands and is transferred to females during reproduction, indicating multiple roles in the mosquito life cycle. However, it is unclear what role it plays in these tissues and what ligands it interacts with. Here we present solution and X-ray crystallographic studies that indicate a potential role of AeOBP22 binding to fatty acids, and that the specifcity for longer chain fatty acids is regulated by a conformational change in the C-terminal tail that leads to creation of an enlarged binding cavity that enhances binding afnity. This study sheds light onto the native ligands for AeOBP22 and provides insight into its potential functions in diferent tissues.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Neutron irradiation-induced microstructure damage in ultra-high temperature ceramic TiC

Titanium carbide (TiC) is an ultra-high temperature ceramic with potential as a structural material candidate for advanced reactor concepts. However, the irradiation tolerance of TiC is not well understood. Here, we reveal the key irradiation damage microstructure degradation processes in TiC using mixed spectrum neutron irradiations at dose of ~2 displacements per atom (dpa) at temperatures of ~220, 620, and 1115 °C, combined with state-of-art microstructure characterization using transmission electron microscopy (TEM) and high-resolution TEM (HRTEM). The helium injection (~65 atomic parts per million) produced by neutron transmutation also occurred in the sample. TiC was observed to form irradiation-induced interstitial-type dislocation loops and He-stabilized cavities. At 220 and 620 °C, the analysis of the electron diffraction patterns, rel-rod imaging and HRTEM revealed that the dislocation loops were faulted Frank loops with Burgers vector b Frank = 1/3<111> lying on {111} planes. A detailed Burgers vector identification performed by the g.b technique revealed that the dislocation loops forming at 1115 °C were unfaulted, edge-type, with Burgers vectors b = a<100> and a/2<110> with corresponding {100} and {110} habit planes. Using continuum mechanics, we estimated the critical radius at which a faulted dislocation loop transitions to a perfect loop to be 9 nm. Further, no amorphization occurred in TiC under-investigated irradiation conditions while macroscopic swelling under point defect swelling regime was observed. He-stabilized cavities were detected at 1115 °C, but not at lower temperature irradiation. These observations indicate the onset of long-range vacancy migration in TiC occurs between 620 and 1115 °C.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Systematic Assessment of Retrieval Methods for Canopy Far-Red Solar-Induced Chlorophyll Fluorescence Using High-Frequency Automated Field Spectroscopy

Remote sensing of solar-induced chlorophyll fluorescence (SIF) offers potential to infer photosynthesis across scales and biomes. Many retrieval methods have been developed to estimate top-of-canopy SIF using ground-based spectroscopy. However, inconsistencies among methods may confound interpretation of SIF dynamics, eco-physiological/environmental drivers, and its relationship with photosynthesis. Using high temporal- and spectral resolution ground-based spectroscopy, we aimed to (1) evaluate performance of SIF retrieval methods under diverse sky conditions using continuous field measurements; (2) assess method sensitivity to fluctuating light, reflectance, and fluorescence emission spectra; and (3) inform users for optimal ground-based SIF retrieval. Analysis included field measurements from bi-hemispherical and hemispherical-conical systems and synthetic upwelling radiance constructed from measured downwelling radiance, simulated reflectance, and simulated fluorescence for benchmarking. Fraunhofer-based differential optical absorption spectroscopy (DOAS) and singular vector decomposition (SVD) retrievals exhibit convergent SIF-PAR relationships and diurnal consistency across different sky conditions, while O2A-based spectral fitting method (SFM), SVD, and modified Fraunhofer line discrimination (3FLD) exhibit divergent SIF-PAR relationships across sky conditions. We find that such behavior holds across system configurations, though hemispherical-conical systems diverge less across sky conditions. O 2 A retrieval accuracy, influenced by atmospheric distortion, improves with a narrower fitting window and when training SVD with temporally local spectra. This may impact SIF-photosynthesis relationships interpreted by previous studies using O 2 A-based retrievals with standard (759–767.76 nm) fitting windows. Fraunhofer-based retrievals resist atmospheric impacts but are noisier and more sensitive to assumed SIF spectral shape than O 2 A-based retrievals. We recommend SVD or SFM using reduced fitting window (759.5–761.5 nm) for robust far-red SIF retrievals across sky conditions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Adaptive machine learning for time-varying systems: low dimensional latent space tuning

Machine learning (ML) tools such as encoder-decoder convolutional neural networks (CNN) can represent incredibly complex nonlinear functions which map between combinations of images and scalars. For example, CNNs can be used to map combinations of accelerator parameters and images which are 2D projections of the 6D phase space distributions of charged particle beams as they are transported between various particle accelerator locations. Despite their strengths, applying ML to time-varying systems, or systems with shifting distributions, is an open problem, especially for large systems for which collecting new data for re-training is impractical or interrupts operations. Particle accelerators are one example of large time-varying systems for which collecting detailed training data requires lengthy dedicated beam measurements which may no longer be available during regular operations. We present a novel method of adaptive ML for time-varying systems. Our approach is to map very high (N ≈ 100k) dimensional inputs (a combination of scalar parameters and images) into the low dimensional (N ≈ 2) latent space at the output of the encoder section of an encoder-decoder CNN. We then actively tune the low dimensional latent space-based representation of complex system dynamics by the addition of an adaptively tuned feedback vector directly before the decoder sections builds back up to our image-based high-dimensional phase space density representations. This method allows us to learn correlations within and to quickly tune the characteristics of incredibly large parameter space systems and to track their evolution in real time based on feedback without massive new data sets for re-training. We demonstrate that our method can accurately predict and track the phase space of charged particle beams at various locations in a particle accelerator by adaptively adjusting in real-time while the unknown input beam distribution of the accelerator is changing in shape, charge, and offset and while the RF system of the accelerator itself is also changing in an unpredictable way. For FACET-II we demonstrate that such an approach has the potential to use transverse deflecting cavity and energy spread spectrum beam measurements to accurately predict 2D projections of the 6D phase space of the electron beam at the plasma wakefield acceleration interaction point where such diagnostics are unavailable.

47 OTHER INSTRUMENTATION↗

NASA NTRS1986

Identification of nonlinear system parameters in joints using the force-state mapping technique

A procedure is presented for identifying the potentially strong nonlinear properties of structural members, such as joints, by expressing the force transmitted by the member as a function of its mechanical state. By explicitly including position and rate dependent effects, the surface of transmitted force versus state, the force-state map, has distinct, unique, superposable features for common structural nonlinearities, even those which appear to indicate hysteresis on a force-stroke presentation. An analysis is performed on the influence of true memory effects, transient response, and uncertainty in the measurements and system mass on the precision of the procedure. The successful identification of simulated data verifies the accuracy of the identification algorithm. Tests are then conducted on three actual joint models, with incomplete state measurements typical of an actual testing environment. The ability of the procedure to estimate the complete state vector and to analyze and reconstruct the measured nonlinear characteristics is demonstrated.

Crawley, E. F.↗

DOE OSTI2025

Quantum mechanical dataset of 836k neutral closed-shell molecules with up to 5 heavy atoms from C, N, O, F, Si, P, S, Cl, Br

Abstract We introduce the Vector-QM24 (VQM24) dataset comprehensively covering all possible neutral closed-shell small organic and inorganic molecules with up to five heavy (p-block) atoms: C, N, O, F, Si, P, S, Cl, Br. All valid stoichiometries, Lewis-rule-consistent graphs, and stable conformers (identified via GFN2-xTB) were enumerated combinatorially, yielding 577k conformational isomers spanning 258k constitutional isomers and 5,599 unique stoichiometries. DFT (ωB97X-D3/cc-pVDZ) optimizations were performed for all, and diffusion quantum Monte Carlo (DMC@PBE0(ccECP/cc-pVQZ)) energies are provided for 10,793 lowest-energy conformers with up to 4 heavy atoms. VQM24 includes structures, vibrational modes, rotational constants, thermodynamic properties (Gibbs free energies, enthalpies, ZPVEs, entropies, heat capacities), and electronic properties such as atomization, electron interaction, exchange-correlation, dispersion energies, multipole moments (dipole to hexadecapole), alchemical potentials, Mulliken charges, and wavefunctions. Machine learning models of atomization energies on this dataset reveal significantly higher complexity than QM9, with none achieving chemical accuracy. VQM24 offers a rigorous, high-fidelity benchmark for evaluating quantum machine learning models.

Science & Technology - Other Topics↗

DOE OSTI2020

Multicarrier Energy Systems: Shaping Our Energy Future

Multicarrier energy systems (MCESs) are characterized by strong coordination in operation and planning across multiple energy vectors and/or sectors to deliver reliable, cost-effective energy services to end users/customers with minimal impact on the environment. They have efficiency and flexibility benefits and are deployed in large and small scales on the supply and demand sides and at the network level but are more complex to control and manage. Here, MCESs are reviewed in the context of future low carbon energy systems based on electrification and very high variable renewable energy penetrations. Fully exploiting these systems requires some cost reductions, more sophisticated operations enabled by standardized communications and control capabilities detailed planning paradigms, and addressing their corresponding economic challenges. All these point toward the direction of analysis, markets, and technology research and development coupled with better policy and regulatory frameworks. One futuristic vision of a very low carbon energy system is proposed that illustrates potential pathways to an MCES-dominated energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

A Computational Theory for the Emergence of Grammatical Categories in Cortical Dynamics

A general agreement in psycholinguistics claims that syntax and meaning are unified precisely and very quickly during online sentence processing. Although several theories have advanced arguments regarding the neurocomputational bases of this phenomenon, we argue that these theories could potentially benefit by including neurophysiological data concerning cortical dynamics constraints in brain tissue. In addition, some theories promote the integration of complex optimization methods in neural tissue. In this paper we attempt to fill these gaps introducing a computational model inspired in the dynamics of cortical tissue. In our modeling approach, proximal afferent dendrites produce stochastic cellular activations, while distal dendritic branches–on the other hand–contribute independently to somatic depolarization by means of dendritic spikes, and finally, prediction failures produce massive firing events preventing formation of sparse distributed representations. The model presented in this paper combines semantic and coarse-grained syntactic constraints for each word in a sentence context until grammatically related word function discrimination emerges spontaneously by the sole correlation of lexical information from different sources without applying complex optimization methods. By means of support vector machine techniques, we show that the sparse activation features returned by our approach are well suited—bootstrapping from the features returned by Word Embedding mechanisms—to accomplish grammatical function classification of individual words in a sentence. In this way we develop a biologically guided computational explanation for linguistically relevant unification processes in cortex which connects psycholinguistics to neurobiological accounts of language. We also claim that the computational hypotheses established in this research could foster future work on biologically-inspired learning algorithms for natural language processing applications.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

Bioreactor Development for CO2-Based In Situ Resource Utilization Manufacturing

Sustainable long-duration manned missions on both the Moon and Mars will require in situ resource utilization (ISRU). Carbon dioxide (CO2) has great potential as a harvestable resource, making up 95% of the atmosphere on Mars and being produced as respiratory waste in spacecraft and future planetary habitats. Through ISRU, biomanufacturing has the capability to produce a near limitless array of products from local space resources. Here, a CO2-based ISRU recombinant protein producing bioreactor and associated biomanufacturing organisms were designed to produce a highly stable carbonic anhydrase (CA). Candidate organisms were selected by growth characterization on acetate and formic acid, carbon substrates that are synthesized via electrochemical conversion of CO2. To improve growth on the CO2 producing substrate formic acid and for direct integration of ISRU CO2, a synthetic Calvin-Benson-Bassam cycle was designed for use in Escherichia coli. Multiplex genetic modification in E. coli was facilitated by a tailored CRISPR/Cas9 and λ red recombineering two-vector system. For expression of CA, a blue light regulated T7 promoter was employed for dynamic and small molecule free induction. Efficient bioproduction through a fed-batch exponential feeding strategy was determined via mass balance analysis from ISRU substrates to biomass and CA yield. Flux balance analysis was used to model ISRU substrate metabolism and metabolic pathway engineering in candidate organisms under cultivation strategy conditions for both metabolism reconstruction and pathway design optimization. Finally, a small-scale, disposable bag bioreactor for use in the NASA Bioculture System infrastructure was designed to enable CO2-based CA biomanufacturing in reduced-gravity environments.

biomanufacturing↗

NASA NTRS2003

CME Prediction from Magnetograms

We have found that active regions that are likely to be CME productive can be identified from measures of their nonpotentiality from magnetograms. We have developed four different measures from vector magnetograms and another that can be obtained from a line-of-sight magnetogram. We find that all five measures are strongly correlated with CME productivity to a similar degree. Hence, all five are roughly equally good predictors of active-region CME productivity. Since the measures all have similar predictive ability, the measures that are easiest to reliably measure are the best for operational forecasting of CMEs. The two best measures are the length of strong-shear main neutral line L(sub SS) (the length of the main neutral line with the magnetic shear angle greater than 45deg and observed transverse field greater than 150G) and the length of strong-gradient main neutral line L(sub G) (the length of the main neutral line with line-of-sight magnetic field greater than 50G/Mm and potential transverse field greater than 150G). As L(sub G) is measured from line-of-sight magnetograms it opens the larger data base of SOHO/MDI and Kitt Peak line-of-sight magnetograms for CME prediction study. This is especially important for evolutionary studies, with SOHO/MDI having no daylight, cloudy weather, or atmospheric seeing problems.

Falconer, D. A.↗

NASA NTRSDate not supplied

Decision Aid for Conjunction Risk Mitigation by Differential Drag

In the previous five years, the rate of conjunctions that the NASA Conjunction Assessment Risk Analysis (CARA) team processed and analyzed has more than tripled. (NASA CARA, 2024) New missions in the early development phases are now required to plan for dealing with conjunctions under the present space environment, and also projecting forward into a future likely with even further increased utilization of the space environment. Some missions are investigating the possibility of using differential drag to remediate conjunctions without expending limited fuel or for missions without propulsive capabilities. The NASA CARA team studied the historical record of conjunctions to evaluate the circumstances under which differential drag may be successfully applied and have developed a series of tables to use as a decision aid for missions considering differential drag. CARA records all conjunctions of their protected payloads, with historical records starting in 2005 (with significant conjunction events starting to occur on or after 2013). From this record, approximately 7,300 had a probability of collision (Pc) greater than 1 in 10,000, the nominal requirement for a risk mitigation maneuver (RMM) to be made per NASA Procedural Requirements (NPR) 8079.1 (NASA, 2023), at 3 days prior to the time of closest approach, the time analyzed for differential drag efficacy. CARA’s maneuver trade space tool (MTS) was used to prop-agate the primary satellite forward from that decision point with varying degrees of increase to ballistic coefficient (BC), and then recalculate the Pc to evaluate whether or not the conjunction was mitigated (Pc < 3E-6). These results were then binned and sorted along several axes, including altitude, amount of delta-BC, and (pre-maneuver) rate of energy dissipation, to identify underlying patterns. The altitude plot is shown in Figure 1. We found that differential drag was most successful for satellites with perigees below 560 km, and which could adopt an average delta-BC of 2 or greater (that is, increasing their ballistic coefficient by a factor of 3). However, this is a difficult threshold for a mission to clear; very few spacecraft are capable of adopting a high-drag configuration for 72 hours continuously. Planet’s Dove spacecraft use differential drag to remediate conjunctions (Griffith, et al., 2021), and they have a maximum delta-BC factor of 9, but in practice (with mission and charging constraints) they achieve a time-averaged delta-BC that is closer to 2 (Foster, et al., 2017). In contrast, a NASA mission in development reached out to CARA to evaluate the utility of differential drag to remediate potential conjunctions for a spacecraft which is capable of a similar high delta-BC, but with operational constraints that limit their time-averaged delta-BC to less than 1. CARA has developed tables that can be used as decision aids to advise missions-in-development about the best way to utilize their differential drag capabilities. For missions below 560 km with the operational flexibility to devote multiple days to holding a high-drag configuration (or a sufficiently high drag ratio to compensate for limitations on that time), they are able to successfully remediate high-risk conjunctions. Conversely, missions that do not meet these ex-acting criteria – most missions – can instead be advised to use on-board propulsion systems to perform RMMs or to turn their minimum-area face towards the approach vector, thereby reducing Pc at the moment of conjunction. (NASA, 2023)

risk mitigation↗