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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The Influence of Mesoscale Particle Structure on the Electrode Degradation and Resultant Electrochemistry of Lithium Ion Cells With Nickel Rich Lithium Nickel Manganese Cobalt Oxide Positive Electrodes

Nickel-rich lithium nickel manganese cobalt oxide, NMC (LiNi x Mn y Co z O 2 ), materials are desirable positive electrodes in lithium ion batteries, providing high capacity and energy density. The mesoscale structure of NMC materials is commonly a polycrystalline aggregate, providing opportunity for short lithium ion transport distance of the small primary particles, yet facile material handling due to the larger secondary particles. On (de)lithiation the NMC unit cell changes volume, where the anisotropic strain can result in secondary particle fracture. This secondary particle fracture process during cycling has been associated with several degradation modes of NMC materials in LIBs. In this work, a milling process was determined whereby the secondary particles could be pre-fractured with retention of the parent primary particle crystallographic structure, crystallite size, and morphology, providing the ability to unambiguously determine the influence of NMC secondary particle size and mesostructure on resultant functional behavior. The bulk and interfacial properties and electrochemistry of as-received commercially obtained polycrystal NMC811 (LiNi 0.8 Mn 0.1 Co 0.1 O 2 , PC NMC) and its milled MPC NMC counterpart were compared. The smaller secondary particle size, higher surface area MPC NMC was found to result in 1) greater cathode tortuosity, 2) reduced surface Ni on the cycled MPC cathodes consistent with surface reconstruction, and 3) increased Ni deposition on the anodes from cathode-anode crosstalk. These factors manifested in unfavorable electrochemical behavior of MPC with lower functional capacity at both 1C and C/10 rates and higher impedance over extended moderate voltage (dis)charge cycling.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Model predictive control of mixing controlled compression ignition operation for low reactivity fuels

Using gasoline or other low reactivity fuels with a pilot injection or port fuel injection in a compression ignition engine has shown great potential in reducing NOx emissions while keeping high thermal efficiency compared to diesel. However, excessive combustion noise is caused by a high maximum pressure rise rate in the cylinder due to the higher fractions of premixed charge of the low-reactivity fuel. This noise can result in structural damage to engine components and as such, combustion noise limits the range of the operating parameters and makes the control of such engines challenging. In this study, a simulation environment was built up in MATLAB/Simulink leveraging a physics-based zero-dimension combustion model to capture the in-cylinder pressure time traces as well as metrics relevant to thermal efficiency and combustion noise. Here, in order to also facilitate the control of emissions, machine learning models were investigated to capture NOx emissions. A kernel-based extreme learning machine (K-ELM) performed best and had a coefficient of correlation (R-squared) of 0.998. The combustion and NOx emission models are valid for not only conventional gasoline fuel but also oxygenated alternative fuel blends at three different pilot injection strategies. In order to track key combustion metrics while keeping noise and emissions within constraints, a model predictive control (MPC) was applied for a compression ignition engine operating with a range of potential fuels and fuel injection strategies. The MPC is validated under different scenarios, including a load step change, fuel type change, and injection strategy change, with proportional–integral (PI) control as the baseline. The simulation results show that MPC reduces about 26% of ringing intensity in the transient process and 17% at the steady state for E30. Generally, MPC can optimize the overall performance through modifying the main injection timing, pilot fuel mass, and exhaust gas recirculation (EGR) fraction.

42 ENGINEERING↗
DOE OSTI2024

Influence of zwitterionic amphiphilic copolymers on heterogeneous gypsum formation: A promising approach for scaling resistance

Here, this study aims to investigate the influence of zwitterionic amphiphilic copolymers (ZACs) in the nucleation and growth of heterogeneous CaSO4 at the zwitterion-water interface, which is crucial for the prevention of mineral scaling and consequent downtime or suboptimal performance in industries like membrane desalination, heat exchangers, and pipeline transportation. In situ grazing incidence small angle X-ray Scattering (GISAXS), and quartz crystal microbalance with dissipation (QCM-D) techniques were used to analyze the evolution of CaSO 4 particles on two new ZAC coatings: poly-(trifluoroethyl methacrylate-random-sulfobetaine methacrylate) (PTFEMA-r-SBMA, or PT:SBMA) and poly(trifluoroethyl methacrylate-random-2-methacryloyloxyethyl phosphorylcholine) (PTFEMA-r-MPC, or PT:MPC). The results showed that PT:MPC coatings promoted nucleation but inhibited crystal growth, resulting in slower overall reaction kinetics on PT:MPC coatings compared to PT:SBMA coatings. Interfacial interactions involving the substrates, sulfate minerals, and ions were examined, revealing that calcium ion adsorption, primarily governed by electrostatic attraction, played a crucial role in the nucleation and growth processes on both ZAC coatings. The crystal characterization revealed a phase transition from bassanite to gypsum on both ZAC coatings, suggesting that these zwitterionic materials can influence the mineral phase of heterogeneously formed CaSO 4 crystals. These findings enhance our understanding of the fundamental mechanisms underlying heterogeneous CaSO 4 scaling in the presence of zwitterionic materials.

42 ENGINEERING↗
DOE OSTI2023

Investigating the large-scale environment of wide-angle tailed radio galaxies in the local Universe

We present a statistical analysis of the large-scale (up to two Mpc) environment of a homogeneous and complete sample, both in radio and optical selection, of wide-angle tailed radio galaxies (WATs) in the local Universe (i.e., with redshifts z ≲ 0.15). The analysis is carried out using the parameters obtained from cosmological neighbors within two Mpc of the target source. Results regarding the large-scale environments of the WATs are then compared with those of Fanaroff–Riley type I (FR Is) and type II (FR IIs) radio galaxies listed in two other homogeneous and complete catalogs and selected with the same criterion adopted for the WATs catalog. We obtain indication that at low redshift, WATs inhabit environments with a larger number of galaxies than those of FR Is and FR IIs. In the explored redshift range, the physical size of the galaxy group or cluster in which the WATs reside appears to be almost constant with respect to FR Is and FR IIs, being around one Mpc. From the distribution of the concentration parameter, defined as the ratio between the number of cosmological neighbors lying within 500 kpc and within one Mpc, we conclude that WATs tend to inhabit the central region of the group or cluster in which they reside, in agreement with the general paradigm that WATs are the brightest cluster or group galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The DESI One-Percent Survey: Modelling the clustering and halo occupation of all four DESI tracers with U CHUU

We present results from a set of mock lightcones for the DESI One-Percent Survey, created from the UCHUU simulation. This 8 h −3 Gpc 3 N-body simulation comprises 2.1 trillion particles and provides high-resolution dark matter (sub)haloes in the framework of the Planck-based ΛCDM cosmology. Employing the subhalo abundance matching (SHAM) technique, we populated the UCHUU (sub)haloes with all four DESI tracers – Bright Galaxy Survey (BGS), luminous red galaxies (LRGs), emission line galaxies (ELGs), and quasars (QSOs) – to z = 2.1. Our method accounts for redshift evolution as well as the clustering dependence on luminosity and stellar mass. The two-point clustering statistics of the DESI One-Percent Survey generally agree with predictions from UCHUU across scales ranging from 0.3 h −1 Mpc to 100 h −1 Mpc for the BGS and across scales ranging from 5 h −1 Mpc to 100 h −1 Mpc for the other tracers. We observed some differences in clustering statistics that can be attributed to incompleteness of the massive end of the stellar mass function of LRGs, our use of a simplified galaxy-halo connection model for ELGs and QSOs, and cosmic variance. We find that at the high precision of UCHUU, the shape of the halo occupation distribution (HOD) of the BGS and LRG samples is smaller bias values, likely due to cosmic variance. The bias dependence on absolute magnitude, stellar mass, and redshift aligns with that of previous surveys. These results provide DESI with tools to generate high-fidelity lightcones for the remainder of the survey and enhance our understanding of the galaxy-halo connection.

cosmology↗
DOE OSTI2024

Hybrid model predictive control techniques for safety factor profile and stored energy regulation while incorporating NBI constraints

Abstract A novel hybrid Model Predictive Control (MPC) algorithm has been designed for simultaneous safety factor ( q ) profile and stored energy ( w ) control while incorporating the pulse-width-modulation constraints associated with the neutral beam injection (NBI) system. Regulation of the q -profile has been extensively shown to be a key factor for improved confinement as well as non-inductive sustainment of the plasma current. Simultaneous control of w is necessary to prevent the triggering of pressure-driven magnetohydrodynamic instabilities as the controller shapes the q profile. Conventional MPC schemes proposed for q -profile control have considered the NBI powers as continuous-time signals, ignoring the discrete-time nature of these actuators and leading in some cases to performance loss. The hybrid MPC scheme in this work has the capability of incorporating the discrete-time actuator dynamics as additional constraints. In nonlinear simulations, the proposed hybrid MPC scheme demonstrates improved q -profile+ w control performance for NSTX-U operating scenarios.

Physics↗
DOE OSTI2021

Galaxy–galaxy lensing with the DES-CMASS catalogue: measurement and constraints on the galaxy-matter cross-correlation

ABSTRACT The DMASS sample is a photometric sample from the DES Year 1 data set designed to replicate the properties of the CMASS sample from BOSS, in support of a joint analysis of DES and BOSS beyond the small overlapping area. In this paper, we present the measurement of galaxy–galaxy lensing using the DMASS sample as gravitational lenses in the DES Y1 imaging data. We test a number of potential systematics that can bias the galaxy–galaxy lensing signal, including those from shear estimation, photometric redshifts, and observing conditions. After careful systematic tests, we obtain a highly significant detection of the galaxy–galaxy lensing signal, with total S/N = 25.7. With the measured signal, we assess the feasibility of using DMASS as gravitational lenses equivalent to CMASS, by estimating the galaxy-matter cross-correlation coefficient rcc. By jointly fitting the galaxy–galaxy lensing measurement with the galaxy clustering measurement from CMASS, we obtain $r_{\rm cc}=1.09^{+0.12}_{-0.11}$ for the scale cut of $4 \, h^{-1}{\rm \,\,Mpc}$ and $r_{\rm cc}=1.06^{+0.13}_{-0.12}$ for $12 \, h^{-1}{\rm \,\,Mpc}$ in fixed cosmology. By adding the angular galaxy clustering of DMASS, we obtain rcc = 1.06 ± 0.10 for the scale cut of $4 \, h^{-1}{\rm \,\,Mpc}$ and rcc = 1.03 ± 0.11 for $12 \, h^{-1}{\rm \,\,Mpc}$. The resulting values of rcc indicate that the lensing signal of DMASS is statistically consistent with the one that would have been measured if CMASS had populated the DES region within the given statistical uncertainty. The measurement of galaxy–galaxy lensing presented in this paper will serve as part of the data vector for the forthcoming cosmology analysis in preparation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The information content of projected galaxy fields

ABSTRACT The power spectrum of the non-linearly evolved large-scale mass distribution recovers only a minority of the information available on the mass fluctuation amplitude. We investigate the recovery of this information in 2D ‘slabs’ of the mass distribution averaged over ≈100 h−1 Mpc along the line of sight, as might be obtained from photometric redshift surveys. We demonstrate a Hamiltonian Monte Carlo method to reconstruct the non-Gaussian mass distribution in slabs, under the assumption that the projected field is a point-transformed Gaussian random field, Poisson-sampled by galaxies. When applied to the Quijote N-body suite at z = 0.5 and at a transverse resolution of 2 h−1 Mpc, the method recovers ∼30 times more information than the 2D power spectrum in the well-sampled limit, recovering the Gaussian limit on information. At a more realistic galaxy sampling density of 0.01 h3 Mpc−3, shot noise reduces the information gain to a factor of 5 improvement over the power spectrum at resolutions of 4 h−1 Mpc or smaller.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Finding evidence for inflation and the origin of galactic magnetic fields with CMB surveys

The origin of the μG magnetic fields observed in galaxies is unknown. One promising scenario is that magnetic fields generated during inflation, larger than 0.1 nG on Mpc scales, were adiabatically compressed to μG strengths in galaxies during structure formation. Thus, detecting a scale-invariant primordial magnetic field (PMF) above 0.1 nG on Mpc scales just after recombination would indicate an inflationary origin of galactic magnetic fields. Furthermore, this would also provide compelling evidence that inflation occurred since only an inflationary mechanism could generate such a strong, scale-invariant magnetic field on Mpc scales. In contrast, constraining the scale-invariant PMF strength to be below 0.1 nG would imply an inflationary scenario is not the primary origin, since such weak PMFs cannot be amplified enough via adiabatic compression to produce the strength of the galactic fields we observe today. We find that measurements of anisotropic birefringence by future CMB surveys will be able to improve the sensitivity to Mpc-scale inflationary PMFs by an order of magnitude, and, in particular, that CMB-HD would lower the upper bound to 0.072 nG at the 95% C.L., which is below the critical 0.1 nG threshold for ruling out a purely inflationary origin. If inflationary PMFs exist, we find that a CMB-HD survey would be able to detect them with about 3σ significance or higher, providing evidence for inflation itself.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Model Predictive Control-Based Trajectory Shaper for Safe and Efficient Adaptive Cruise Control

Recent studies show that commercially-available adaptive cruise control (ACC) systems are string-unstable, indicating that ACC-driven vehicles amplify speed fluctuations from downstream traffic and induce stop-and-go waves. Moreover, it is challenging to revise the original control algorithm of an ACC system to achieve string stability due to its internal complexity and powertrain uncertainties. To achieve desired control performance given a string-unstable ACC system and circumvent revising the original control algorithm, this study proposes a model predictive control-based trajectory shaper (MPC-TS), which only modifies the sensor-measured trajectory information (i.e., position and speed) of the preceding vehicle. The proposed MPC-TS leverages the input shaping technique to generate reference trajectory to improve string stability, while incorporating tracking errors and vehicle acceleration/deceleration magnitude in the MPC cost function and constraining fluctuations of vehicle speed and spacing to ensure desired car-following performance. Numerical experiments validate the control performance of ACC with the proposed MPC-TS in terms of string stability, safety, traffic efficiency, and comfort.

Zhou, Anye↗
DOE OSTI2024

Robust Data-Driven Predictive Run-to-Run Control for Automated Serial Sectioning

This letter presents a one-step predictive run-to-run controller (R2R-MPC) for the automation of mechanical serial sectioning (MSS), a destructive material analysis process. To address the inherent uncertainty and disturbances in the MSS process, a robust closed-loop approach is presented. Here, the robust R2R-MPC models the uncertainty of the MSS process using a linear differential inclusion. As an analytical model of the MSS process is unavailable, the differential inclusion is identified from historical data. The R2R-MPC is posed as an optimization problem that computes incremental changes to the control input which minimize the worst-case material removal errors. This optimization-based controller is combined with a run-to-run controller to provide integral action that rejects constant disturbances and tracks constant reference removal rates. To demonstrate the efficacy of our robust R2R-MPC, we present simulation results which compare the presented controller with a conventional non-robust R2R.

42 ENGINEERING↗
DOE OSTI2022

MPC4CLR (Model-Predictive-Control-for-Critical-Load-Restoration-in-Power-Distribution-Systems) [SWR-22-24]

Model predictive control (MPC) is a system or process control technique for making decisions under uncertainty via rolling look-ahead optimizations at each control step where only the current step decisions are applied, and the rest are discarded. In this work, we developed an MPC for a critical load restoration (CLR) in power distribution systems to recover system service (electricity delivery) following an extreme event-triggered substation outage. The method considers the problem of controlling distributed energy resources (DERs) of the distribution system with the objective of achieving maximum load pick up while satisfying distribution network flow and voltage constraints. A linearized optimal power flow (OPF) model is employed to represent the physics of the network. The problem formulation is augmented with a ramping (up) reserve product for the DERs to ensure improved and upward monotonic load restoration as time evolves. Simulation analysis and performance tests are performed using a modified IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage battery. The software is developed using various software packages in Julia and Python. The MPC model is implemented using the JuMP optimization language in Julia while the data analytics including renewable generation and load demand forecasts, running the MPC simulation and visualizations is performed in Python.

Eseye, Abinet Tesfaye↗
DOE OSTI2024

How the Galaxy–Halo Connection Depends on Large-scale Environment

We investigate the connection between galaxies, dark matter halos, and their large-scale environments at z = 0 with Illustris TNG300 hydrodynamic simulation data. We predict stellar masses from subhalo properties to test two types of machine learning (ML) models: explainable boosting machines (EBMs) with simple galaxy environment features and E(3)-invariant graph neural networks (GNNs). The best-performing EBM models leverage spherically averaged overdensity features on 3 Mpc scales. Interpretations via SHapley Additive exPlanations also suggest that in the context of the TNG300 galaxy–halo connection, simple spherical overdensity on ∼3 Mpc scales is more important than cosmic web distance features measured using the DisPerSE algorithm. Meanwhile, a GNN with connectivity defined by a fixed linking length, L, outperforms the EBM models by a significant margin. As we increase the linking length scale, GNNs learn important environmental contributions up to the largest scales we probe (L = 10 Mpc). We conclude that 3 Mpc distance scales are most critical for describing the TNG galaxy–halo connection using the spherical overdensity parameterization, but that information on larger scales, which is not captured by simple environmental parameters or cosmic web features, can further augment these models. Our study highlights the benefits of using interpretable ML algorithms to explain models of astrophysical phenomena, and the power of using GNNs to flexibly learn complex relationships directly from data while imposing constraints from physical symmetries.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

The Chicago Carnegie Hubble Program: Improving the Calibration of Type Ia Supernovae with JWST Measurements of the Tip of the Red Giant Branch

We present distances to 10 supernova (SN) host galaxies determined via the tip of the red giant branch using JWST/NIRCam and the F115W, F356W, and F444W bandpasses. The majority of the analysis was conducted on photometric catalogs that had their absolute zero-points randomized to mask information on distance. The new F115W TRGB distances, anchored by the geometric maser distance to NGC 4258, agree well with our previously derived Hubble Space Telescope (HST) TRGB distances, differing by only 1% on average and 4% on a per-galaxy basis. The color-corrected F115W TRGB is therefore equally precise a method of distance measurement as, and offers unique advantages over, its color-insensitive, I-band counterpart. We use these distances to update four published H 0 calibrations and evaluate how different SN analyses, both within and across independent groups, yield different H 0 values. For our JWST sample of 11 SNe, we find consistent values of H 0 ≃ 69 km s −1 Mpc −1 , with a dispersion of just 0.6 km s −1 Mpc −1 across the updated calibrations. When we expand the sample to 24 by combining with HST TRGB measurements, the results from different SN analyses begin to diverge, with the H 0 based on Pantheon+ and the Carnegie Supernova Project II (CSP-II), respectively, increasing by +2.0 km s −1 Mpc −1 (3.1σ significance) and +0.8 km s −1 Mpc −1 (1.4σ significance). More independent analyses of low-redshift SNe and JWST observations of the TRGB are needed to improve our understanding of systematics in distance ladder determinations of H 0 .

Hoyt, Taylor J. [Lawrence Berkeley National Labora↗
DOE OSTI2024

Three Quenched, Faint Dwarf Galaxies in the Direction of NGC 300: New Probes of Reionization and Internal Feedback

We report the discovery of three faint and ultra-faint dwarf galaxies -- Sculptor A, Sculptor B and Sculptor C -- in the direction of NGC 300 (D=2.0 Mpc), a Large Magellanic Cloud-mass galaxy. Deep ground-based imaging with Gemini/GMOS resolves all three dwarf galaxies into stars, each displaying a red giant branch indicative of an old, metal-poor stellar population. No young stars or HI gas are apparent, and the lack of a GALEX UV detection suggests that all three systems are quenched. Sculptor C (D=2.04$^{+0.10}_{-0.13}$ Mpc; $M_V=-9.1\pm 0.1$ mag or $L_V=(3.7^{+0.4}_{-0.3})\times 10^5L_{\odot})$ is consistent with being a satellite of NGC 300. Sculptor A (D=1.35$^{+0.22}_{-0.08}$ Mpc; $M_V=-6.9\pm 0.3$ mag or $L_V=(5^{+1}_{-1})\times 10^4 L_{\odot})$ is likely in the foreground of NGC 300 and at the extreme edge of the Local Group, analogous to the recently discovered ultra-faint Tucana B in terms of its physical properties and environment. Sculptor B (D=2.48$^{+0.21}_{-0.24}$ Mpc; $M_V=-8.1\pm 0.3$ mag or $L_V=(1.5^{+0.5}_{-0.4})\times 10^5L_{\odot})$ is likely in the background, but future distance measurements are necessary to solidify this statement. It is also of interest due to its quiescent state and low stellar mass. Both Sculptor A and B are $\gtrsim 2-4 r_{vir}$ from NGC 300 itself. The discovery of three dwarf galaxies in isolated or low-density environments offers an opportunity to study the varying effects of ram pressure stripping, reionization and internal feedback in influencing the star formation history of the faintest stellar systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

MOSAiC studies of long-lasting mixed-phase cloud events and analysis of the liquid-phase properties of Arctic clouds

Vertically resolved observations of the temporal evolution of mixed-phase clouds (MPCs) were performed over the central Arctic during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, which lasted from October 2019 to September 2020. The research icebreaker Polarstern , drifting with the pack ice for more than 7 months, mostly at latitudes > 85° N, served as a platform for state-of-the-art remote sensing of aerosols and clouds. The use of the recently introduced dual field-of-view (FOV) polarization lidar technique in combination with the well-established lidar-radar retrieval technique provided, for the first time, a robust instrumental basis to monitor the evolution of the liquid and the ice phase of MPCs and the interplay between the two phases. Two long-lasting Arctic MPC events observed close to the North Pole in mid-winter (December 2019) and late summer (September 2020) are discussed to provide new insight into Arctic MPC evolution processes. In the second part of the article, cloud statistics, covering all seasons of a year, are presented. The focus is on the optical and microphysical properties of the liquid phase. These results are solely derived from the dual-FOV lidar observations. The key findings of the study can be summarized as follows: persistent activation of aerosol particles to form water droplets is of great importance for the longevity of MPCs. The observations confirm that ice formation occurs predominantly via immersion freezing. The field studies suggest that the free tropospheric reservoirs of cloud condensation nuclei (CCN) and of ice-nucleating particles (INPs) were always well filled, i.e., the clouds did not exhaust their supply of activatable and activated particles. The observation of long-lasting MPC events, low ice production rates, and a sufficiently large INP reservoir leads to the recommendation to use a time-dependent immersion freezing parameterization in MPC modeling efforts.

Jimenez, Cristofer [Leibniz Inst. for Tropospheric↗
NASA NTRS1980

The Hercules supercluster. II - Analysis

The almost complete sample of more than 150 redshifts for galaxies brighter than m sub p = 15.8 mag in a 28 square degree field in Hercules by Tarenghi et al. is used to examine the cosmography of a 60,000 cubic Mpc conical volume of space. It contains a supercluster of Abell clusters with a depth of about 100 Mpc, a vacant 'void' also with a depth of about 100 Mpc, and a structure wider than 12 Mpc which could be part of a more extensive system of small groups of galaxies. Properties of individual rich clusters in the Hercules supercluster are derived, but they are uncertain because the clusters merge into one another, so that it is difficult to identify them and their member galaxies unambiguously. However, those regions in Hercules containing the largest proportion of early-type galaxies show the least evidence for gravitational relaxation. A difference may exist between the luminosity function of clusters of galaxies and the luminosity function of the foreground sheet.

Tarenghi, M.↗
NASA NTRS1989

Surface brightness fluctuations and the distance to the Virgo Cluster

Preliminary results from a project to measure the fluxes of giant stars in M32, NGC 3379, and five Virgo Cluster galaxies are presented. Since the Virgo Cluster galaxies are approximately equidistant, variations in observed fluctuation amplitude from galaxy to galaxy can be ascribed to variations in absolute luminosity of the giant stars in the galaxies. Assuming a distance of 0.72 Mpc for M32 and correcting for the color effect in m-bar, the typical brightness of giant stars, distances of 9 Mpc for NGC 3379 and 14 Mpc for Virgo, accurate to about 10 percent, are derived. This is used to find a Hubble constant of 88 km/s/Mpc. The method can be used to measure m-bar in galaxies at least 40-50 Mpc distant.

Tonry, John L.↗