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At least 1,027 records · Page 57

Uncertainty Analysis of Instrument Calibration and Application

Experimental aerodynamic researchers require estimated precision and bias uncertainties of measured physical quantities, typically at 95 percent confidence levels. Uncertainties of final computed aerodynamic parameters are obtained by propagation of individual measurement uncertainties through the defining functional expressions. In this paper, rigorous mathematical techniques are extended to determine precision and bias uncertainties of any instrument-sensor system. Through this analysis, instrument uncertainties determined through calibration are now expressed as functions of the corresponding measurement for linear and nonlinear univariate and multivariate processes. Treatment of correlated measurement precision error is developed. During laboratory calibration, calibration standard uncertainties are assumed to be an order of magnitude less than those of the instrument being calibrated. Often calibration standards do not satisfy this assumption. This paper applies rigorous statistical methods for inclusion of calibration standard uncertainty and covariance due to the order of their application. The effects of mathematical modeling error on calibration bias uncertainty are quantified. The effects of experimental design on uncertainty are analyzed. The importance of replication is emphasized, techniques for estimation of both bias and precision uncertainties using replication are developed. Statistical tests for stationarity of calibration parameters over time are obtained.

Tripp, John S.↗

Core Model Proposal #399: Updating the SSP Database (v3.0) (Population, GDP, and Labor Force) and Labor Productivity (KLEM)

This Core Model Proposal (CMP) updates the Shared Socioeconomic Pathway (SSP) database to a recent version (v3.0.1; released in 2024) within GCAM. Currently, GCAM relies on socioeconomic drivers, including population, GDP, and labor force projections, from the original SSP database version released in 2013. These projections, provided by independent socioeconomic dynamic models (e.g., multi-dimensional demographic models and macroeconomic models of convergence growth), may need regular updates when (1) near-term observations become available and (2) there are updates and advancements in the socioeconomic modeling. Timely updates of socioeconomic drivers in global economic equilibrium and multisector dynamic modeling will ensure (1) alignment of historical years and near-term projections with observations, enhancing base year calibrations, including calibration parameters and labor productivity, and (2) improvement of long-term projections with updated socioeconomic drivers, which set the scale of the economy. This CMP updates the SSP data (from v2013 to v2024) and also fixes/reconciles historical GDP data sources in GCAM. We investigate the impact of these updates on GCAM projections.

97 MATHEMATICS AND COMPUTING↗

Deep reinforcement learning control for co-optimizing energy consumption, thermal comfort, and indoor air quality in an office building

With the recent demand for decarbonization and energy efficiency, advanced HVAC control using Deep Reinforcement Learning (DRL) becomes a promising solution. Due to its flexible structures, DRL has been successful in energy reduction for many HVAC systems. However, only a few researches applied DRL agents to manage the entire central HVAC system and control multiple components in both the water loop and the air loop, owing to its complex system structures. Moreover, those researches have not extended their applications by incorporating the indoor air quality, especially both CO2 and PM2.5concentrations, on top of energy saving and thermal comfort, as achieving those objectives simultaneously can cause multiple control conflicts. What's more, DRL agents are usually trained on the simulation environment before deployment, so another challenge is to develop an accurate but relatively simple simulator. Therefore, we propose a DRL algorithm for a central HVAC system to co-optimize energy consumption, thermal comfort, indoor CO2 level, and indoor PM2.5 level in an office building. To train the controller, we also developed a hybrid simulator that decoupled the complex system into multiple simulation models, which are calibrated separately using laboratory test data. The hybrid simulator combined the dynamics of the HVAC system, the building envelope, as well as moisture, CO2, and particulate matter transfer. Three control algorithms (rule-based, MPC, and DRL) are developed, and their performances are evaluated on the hybrid simulator environment with a realistic scenario (i.e., with stochastic noises). The test results showed that, the DRL controller can save 21.4 % of energy compared to a rule-based controller, and has improved thermal comfort, reduced indoor CO2 concentration. The MPC controller showed an 18.6 % energy saving compared to the DRL controller, mainly due to savings from comfort and indoor air quality boundary violations caused by unmeasured disturbances, and it also highlights computational challenges in real-time control due to non-linear optimization. Finally, we provide the practical considerations for designing and implementing the DRL and MPC controllers based on their respective pros and cons.

Guo, Fangzhou↗

Establishing a process-structure-property-performance framework for SLS additive manufacturing through integrated multiscale modeling

This study presents a comprehensive suite of high-fidelity computational models that integrate multiscale and multiphysics simulations to capture the full Selective Laser Sintering (SLS) additive manufacturing process—from initial melting and solidification to mechanical response under external loads. Process simulations are linked with mechanical analysis through Representative Volume Elements (RVEs), establishing a process-structure–property-performance framework. The interaction between laser light and polyamide 12 (PA12) powder is modeled, accounting for laser characteristics and the optical, thermal, and geometrical properties of the powder. The heat source is incorporated into a heat transfer model, coupled with crystallization kinetics and densification models to predict material density and crystallinity. The porosity distribution from the densification model and crystallinity interpolated from experimental data are used to construct the RVEs. A multi-mechanism constitutive model is then calibrated using mechanical tests to predict the stress–strain response. Simulation results show good agreement with experimental data in terms of porosity, crystallinity, and mechanical performance when sufficient laser power (62 W or higher) is used. This research supports the inverse design of 3D-printed structures by introducing a high-fidelity framework that combines multiscale and multiphysics modeling with experimental calibration for predictive and performance-driven additive manufacturing.

SLS↗

Testing Small CPAS Parachutes Using HIVAS

The High Velocity Airflow System (HIVAS) facility at the Naval Air Warfare Center (NAWC) at China Lake was successfully used as an alternative to flight test to determine parachute drag performance of two small Capsule Parachute Assembly System (CPAS) canopies. A similar parachute with known performance was also tested as a control. Realtime computations of drag coefficient were unrealistically low. This is because HIVAS produces a non-uniform flow which rapidly decays from a high central core flow. Additional calibration runs were performed to characterize this flow assuming radial symmetry from the centerline. The flow field was used to post-process effective flow velocities at each throttle setting and parachute diameter using the definition of the momentum flux factor. Because one parachute had significant oscillations, additional calculations were required to estimate the projected flow at off-axis angles. The resulting drag data from HIVAS compared favorably to previously estimated parachute performance based on scaled data from analogous CPAS parachutes. The data will improve drag area distributions in the next version of the CPAS Model Memo.

Ray, Eric S.↗

Planetary Spectrum Generator: An Accurate Online Radiative Transfer Suite for Atmospheres, Comets, Small Bodies and Exoplanets

We have developed an online radiative-transfer suite (https://psg.gsfc.nasa.gov) applicable to a broad range of planetary objects (e.g., planets, moons, comets, asteroids, TNOs, KBOs, exoplanets). The Planetary Spectrum Generator (PSG) can synthesize planetary spectra (atmospheres and surfaces) for a broad range of wavelengths (UV/Vis/near-IR/IR/far-IR/THz/sub-mm/Radio) from any observatory (e.g., JWST, ALMA, Keck, SOFIA), any orbiter (e.g., ExoMars, Juno), or any lander (e.g., MSL). This is achieved by combining several state-of-the-art radiative transfer models, spectroscopic databases and planetary databases (i.e., climatological and orbital). PSG has a 3D (three-dimensional) orbital calculator for most bodies in the solar system, and all confirmed exoplanets, while the radiative-transfer models can ingest billions of spectral signatures for hundreds of species from several spectroscopic repositories. It integrates the latest radiative-transfer and scattering methods in order to compute high resolution spectra via line-by-line calculations, and utilizes the efficient correlated-k method at moderate resolutions, while for computing cometary spectra, PSG handles non-LTE and LTE excitation processes. PSG includes a realistic noise calculator that integrates several telescope/instrument configurations (e.g., interferometry, coronagraphs) and detector technologies (e.g., CCD, heterodyne detectors, bolometers). Such an integration of advanced spectroscopic methods into an online tool can greatly serve the planetary community, ultimately enabling the retrieval of planetary parameters from remote sensing data, efficient mission planning strategies, interpretation of current and future planetary data, calibration of spectroscopic data, and development of new instrument/spacecraft concepts.

Villanueva, G. L.↗

VESIcal: An Open-source Thermodynamic Model Engine for Mixed Volatile (H2O-CO2) Solubility in Silicate Melts

Modeling the solubility of volatiles in silicate melts is fundamental to the interpretation of volcanic systems and has implications for magma dynamics, eruption style, and material transport between the mantle, crust, and atmosphere. Recent advancements in computational capabilities and access to computing tools has outpaced the functionality and extensibility of previously available modeling platforms. Here we present VESIcal (Volatile Equilibria and Saturation Index calculator), the first comprehensive modeling tool for H2O, CO2, and mixed (H2O-CO2) solubility in silicate melts that: a) allows users access to seven popular models, with easy inter-comparison between models; b) provides universal functionality for all models (e.g., functions for calculating saturation pressures, degassing paths, etc.); c) can process large datasets (1,000’s of samples) automatically; d) can output computed data into an Excel spreadsheet or CSV file for post-modeling analysis; e) integrates plotting capabilities directly within the tool; and f) provides all of this within the framework of a python library, making the tool extensible by the user and allowing any of the model functions to be incorporated into any other code capable of calling python.Here we will provide a demonstration of VESIcal and its capabilities with applications to various volcanic processes affected by volatiles. VESIcal represents the first tool capable of directly comparing multiple solubility models and equations of state. We find that commonly used models predict surprisingly different volatile solubilities, particularly for pure CO2 or mixed CO2-H2O fluids. Even for melt compositions that are well represented in the calibration datasets of multiple models (e.g., MORBs), calculated solubilities for pure CO2 and pure H2O can deviate from one another by factors of >2 leading to 2x deviations in calculated saturation pressures (e.g., 5 to 10 kbar). The solubility of CO2 predicted by different rhyolitic models also differs substantially, overwhelming other sources of uncertainty such as analytical errors on measurements of volatile contents or uncertainties in crustal density profiles. This highlights the importance of model choice when drawing geological conclusions based on volatiles in magmas.

Kayla Iacovino↗

An open source analysis framework for large-scale building energy modeling

Full integration of building energy modelling into the design and retrofit process has long been a goal of building scientists and practitioners. However, significant barriers still exist. Among them are the lack of available: (1) configurable technology stacks for performing both small- and large-scale analyses, (2) different classes of algorithms compatible with common design workflows, and (3) analysis tools for effectively visualizing large-scale simulation results. This article discusses the OpenStudio® Analysis Framework: a scalable analysis framework for building energy modelling that was developed to overcome the three barriers listed above. The framework is open-source and scalable to facilitate wider adoption and has a clearly defined application programming interface upon which other applications can be built. It runs on high-performance computing systems, within cloud infrastructure, and on laptops, and uses a common workflow to enable different classes of algorithms. Lessons learned from previous development efforts are also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

One‐at‐a‐Time Parameter Perturbation Ensemble of the Community Land Model, Version 5.1

Comprehensive land models are subject to significant parametric uncertainty, which can be hard to quantify due to the large number of parameters and high model computational costs. We constructed a large parameter perturbation ensemble (PPE) for the Community Land Model version 5.1 with biogeochemistry configuration (CLM5.1-BGC). We performed more than 2,000 simulations perturbing 211 parameters across six forcing scenarios. This provides an expansive data set, which can be used to identify the most influential parameters on a wide range of output variables globally, by biome, or by plant functional type. We found that parameter effects can exceed scenario effects and that a small number of parameters explains a large fraction of variance across our ensemble. The most important parameters can differ regionally and also based on the forcing scenario. The software infrastructure developed for this experiment has greatly reduced the human and computer time needed for CLM PPEs, which can facilitate routine investigation of parameter sensitivity and uncertainty, as well as automated calibration.

Kennedy, Daniel [NSF National Center for Atmospher↗

Flame acceleration and transition to detonation in a pre-/main-chamber combustion system

Numerical simulations are performed to study the mechanism of deflagration to detonation transition (DDT) in a pre-/main-chamber combustion system with a stoichiometric ethylene–oxygen mixture. A Godunov algorithm, fifth-order in space, and third-order in time, is used to solve the fully compressible Navier–Stokes equations on a dynamically adapting mesh. A single-step, calibrated chemical diffusive model described by Arrhenius kinetics is used for energy release and conservation between the fuel and the product. The two-dimensional simulation shows that a laminar flame grows in the pre-chamber and then develops into a jet flame as it passes through the orifice. A strong shock forms immediately ahead of the flame, reflecting off the walls and interacting with the flame front. The shock–flame interactions are crucial for the development of flame instabilities, which trigger the subsequent flame development. The DDT arises due to a shock-focusing mechanism, where multiple shocks collide at the flame front. A chemical explosive mode analysis (CEMA) criterion is developed to study the DDT ignition mode. Preliminary one-dimensional computations for a laminar propagating flame, a fast flame deflagration, and a Chapman–Jouguet detonation are conducted to demonstrate the validity of CEMA on the chemical-diffusive model, as well as to determine the proper conditioning value for CEMA diagnostic. The two-dimensional analysis with CEMA indicates that the DDT initiated by the shock-focusing mechanism can form a strong thermal expansion region at the flame front that features large positive eigenvalues for the chemical explosive mode and dominance of the local autoignition mode. Thus, the CEMA criterion proposed in this study provides a robust diagnostic for identifying autoignition-supported DDT, of which the emergence of excessive local autoignition mode is found to be a precursor. The effect of grid size, initial temperature, and orifice size are then evaluated, and results show that although the close-chamber DDT is highly stochastic, the detonation initiation mechanism remains robust.

42 ENGINEERING↗

Theoretical study of the dissociation energy and the red and violet band systems of CN

The dissociation energy (D sub O) of CN is determined to be 7.65 + or - 0.06 eV. This corresponds to delta H sub f (CN) = 105.3 + or - 1.5 kcal/mole, in excellent agreement with Engleman and Rouse (1975), but considerably larger than the recent value deduced from shock-tube studies by Colket (1984). The result is obtained not only from extensive ab initio MRCI calculations using a very large Gaussian basis set, but also from extrapolation of the directly computed value by comparison of computed and experimental results fo NO, C2, and N2. As an additional calibration of the methods, the D sub O value for CN was computed from the corresponding value for CN(-) using the experimental electron affinity data. The lifetime of the nu prime = 0 level of the violet (B 2 sigma + yields X 2 sigma +) system was computed to be 62.4 ns, in good agreement with both experiment and previous calculations. Lifetimes for the red (A 2 pi yields X 2 sigma +) system decrease with increasing nu prime, which is consistent both with the recent experiment and calculations. While the computed lifetimes are significantly longer that those obtained from the experiment, they are shorter than those deduced from an analysis of the solar spectrum. However the D sub O and f (sub OO) are consistent with Lambert's model for the solar spectrum.

Bauschlicher, Charles W., Jr.↗

Operating capability and current status of the reactivated NASA Lewis Research Center Hypersonic Tunnel Facility

The NASA Lewis Research Center's Hypersonic Tunnel Facility (HTF) is a free-jet, blowdown propulsion test facility that can simulate up to Mach-7 flight conditions with true air composition. Mach-5, -6, and -7 nozzles, each with a 42 inch exit diameter, are available. Previously obtained calibration data indicate that the test flow uniformity of the HTF is good. The facility, without modifications, can accommodate models approximately 10 feet long. The test gas is heated using a graphite core induction heater that generates a nonvitiated flow. The combination of clean-air, large-scale, and Mach-7 capabilities is unique to the HTF and enables an accurate propulsion performance determination. The reactivation of the HTF, in progress since 1990, includes refurbishing the graphite heater, the steam generation plant, the gaseous oxygen system, and all control systems. All systems were checked out and recertified, and environmental systems were upgraded to meet current standards. The data systems were also upgraded to current standards and a communication link with NASA-wide computers was added. In May 1994, the reactivation was complete, and an integrated systems test was conducted to verify facility operability. This paper describes the reactivation, the facility status, the operating capabilities, and specific applications of the HTF.

Thomas, Scott R.↗

Operating capability and current status of the reactivated NASA Lewis Research Center hypersonic tunnel facility

The NASA Lewis Research Center's Hypersonic Tunnel Facility (HTF) is a free-jet, blowdown propulsion test facility that can simulate up to Mach-7 flight conditions with true air composition. Mach-5, -6, and -7 nozzles, each with a 42-in. exit diameter, are available. Previously obtained calibration data indicate that the test flow uniformity of the HTF is good. The facility, without modifications, can accomodate models approximately 10 ft long. The test gas is heated using a graphite core induction heater that generates a nonvitiated flow. The combination of clean-air, large-scale, and Mach-7 capabilities is unique to the HTF and enables an accurate propulsion performance determination. The reactivation of the HTF, in progress since 1990, includes refurbishing the graphite heater, the steam generation plant, the gaseous oxygen system, and all control systems. All systems were checked out and recertified, and environmental systems were upgraded to meet current standards. The data systems were also upgraded to current standards and a communication link with NASA-wide computers was added. In May 1994, the reactivation was complete, and an integrated systems test was conducted to verify facility operability. This paper describes the reactivation activities, the facility status, the operating capabilities, and specific applications of the HTF.

Thomas, S.↗

Using Lunar Observations to Validate Pointing Accuracy and Geolocation, Detector Sensitivity Stability and Static Point Response of the CERES Instruments

Validation of in-orbit instrument performance is a function of stability in both instrument and calibration source. This paper describes a method using lunar observations scanning near full moon by the Clouds and Earth Radiant Energy System (CERES) instruments. The Moon offers an external source whose signal variance is predictable and non-degrading. From 2006 to present, these in-orbit observations have become standardized and compiled for the Flight Models -1 and -2 aboard the Terra satellite, for Flight Models-3 and -4 aboard the Aqua satellite, and beginning 2012, for Flight Model-5 aboard Suomi-NPP. Instrument performance measurements studied are detector sensitivity stability, pointing accuracy and static detector point response function. This validation method also shows trends per CERES data channel of 0.8% per decade or less for Flight Models 1-4. Using instrument gimbal data and computed lunar position, the pointing error of each detector telescope, the accuracy and consistency of the alignment between the detectors can be determined. The maximum pointing error was 0.2 Deg. in azimuth and 0.17 Deg. in elevation which corresponds to an error in geolocation near nadir of 2.09 km. With the exception of one detector, all instruments were found to have consistent detector alignment from 2006 to present. All alignment error was within 0.1o with most detector telescopes showing a consistent alignment offset of less than 0.02 Deg.

Daniels, Janet L.↗

Dynamic Behavior of Natural Seep Vents: Analysis of Field and Laboratory Observations and Modeling (Final Scientific/Technical Report)

In this project, we have analyzed data collected by the U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) in a high pressure water tunnel (HPWT) and data from two research cruises to natural seeps in the Gulf of Mexico to adapt and validate a numerical model to predict the dynamics of natural seeps in the deep oceans. The HPWT data include video observations of the shrinkage rate of individual methane and natural gas bubbles under simulated deep-water conditions. Field data were collected during two cruises by the Gulf Integrated Spill Research (GISR) Consortium led by Texas A&M University and funded by the Gulf of Mexico Research Initiative (GoMRI). These data included in situ observations from a remotely operated vehicle (ROV) of gas bubbles at two natural seep sites in the Gulf and acoustic observations of the natural seep bubble flares in the ocean water column. The acoustic data were from multibeam echosounders, one mounted in a forward-looking orientation on the ROV and another mounted down-looking in the haul of the ship. All of these laboratory and field data were focused on the dynamics of natural gas bubbles at temperatures and pressures favorable for clathrate hydrate formation between the gas and water. Our analyses of this data focused on understanding the mechanisms responsible for gas bubble dissolution within the hydrate stability zone (HSZ) of the oceans. Ice-like hydrate shells may form on the bubble-water interface under these conditions, and it was unknown how this might affect the mass transfer of gas into the ocean. We were able to extract bubble shrinkage rates from the HPWT datasets. Using this data we determined that mass transfer coefficients with and without a hydrate shell match empirical values for bubbles in contaminated systems (so-called dirty bubbles contaminated by naturally occurring surfactants). We also showed that free gas, and not gas hydrate, is the dominant dissolving phase when the hydrate sub-cooling is below 11 degree Celsius (temperature difference between hydrate the hydrate formation temperature and ambient temperator) or the pressure is reducing as bubbles rise through the ocean water column. Using this mass transfer model, our numerical model of bubble dissolution matched the over 200 HPWT experiments with an average error of 10% for predicting the bubble size at the end of an experiment. From field data in the literature, we also observed that gas bubbles dissolve faster when they are initially released, following mass transfer coefficients for so-called clean-bubbles (those not yet contaminated by surfactants). Shortly after release within the HSZ, a hydrate shell forms on the bubble-water interface, and the mass transfer reduces to rates matching those of dirty bubbles. We correlated this transition time from clean to dirty bubble behavior with the initial bubble surface area and the hydrate sub-cooling. With this model for hydrate formation time and using the mass transfer coefficients deduced from the HPWT data, we validated our numerical model for predicting the rise heights of natural seep flares in the oceans. Flare heights are commonly observed in haul-mounted acoustic multibeam data. The numerical model predicts bubbles to rise high in the ocean water column owing to the slower mass transfer rates for dirty bubbles that accompany the majority of their rise time. We found that the numerical model predictions matched the observed flare heights within 5% to 10% accuracy when we compared the rise heights of the largest bubbles released from the seafloor with the bubbles acoustically visible in the multibeam data. Bubbles become acoustically transparent as they shrink to sizes of order 1 mm in diameter for the multibeam frequencies used in the field. The forward-looking multibeam on the ROV also provided data on the lateral spreading of bubbles in natural seep flares. Our analysis of this data showed that spreading follows a diffusion process, with the effective diffusivity correlating with the wobbling length scale of these ellipsoidal bubbles. When we apply this diffusivity in a random displacement model of bubble spreading, our numerical simulations match closely the lateral spread observed by the M3 in the ocean water column. Finally, we compared the seep model predictions for the acoustic properties of these natural seep plumes with that observed by the acoustic instruments in the field. The M3 and EM 302 observations were converted to relative values of target strength using a calibration we obtained in the laboratory for the M3 and using an algorithm from the manufacturer for the EM 302. Comparing the numerical seep model to these data, we obtain good agreement over the whole height of rise of these bubble flares. This further validates the numerical model. Overall, our validated seep model captures the key dynamics of gas bubbles released from natural seeps in the oceans and helps to predict the fate of methane in the water column.

03 NATURAL GAS↗

Experimentation and Modeling of Jet A Thermal Stability in a Heated Tube

High performance aircraft typically use hydrocarbon fuel to regeneratively cool the airframe and engine components. As the coolant temperatures increase, the fuel may react with dissolved oxygen forming deposits that limit the regenerative cooling system performance. This study investigates the deposition of Jet A using a thermal stability experiment and computational fluid dynamics (CFD) modeling. The experimental portion of this study is performed with a high Reynolds number thermal stability (HiRets) tester in which fuel passes though an electrically heated tube and the fuel outlet temperature is held constant. If the thermal stability temperature of the fuel is exceeded, deposits form and adhere to the inside of the tube creating an insulating layer between the tube and the fuel. The HiRets tester measures the tube outer wall temperatures near the fuel outlet to report the effect of deposition occurring inside the tube. Final deposits are also estimated with a carbon burn off analysis. The CFD model was developed and used to simulate the fluid dynamics, heat transfer, chemistry, and transport of the deposit precursors. The model is calibrated to the experiment temperature results and carbon burn-off deposition results. The model results show that the dominant factor in deposition is the heated wall temperature and that most of the deposits are formed in the laminar sublayer. The models predicted a 7.0E-6 kilograms per square meter-sec deposition rate, which compared well to the carbon burn-off analysis deposition rate of 1.0E-6 kilograms per square meter-sec.

Khodabandeh, Julia W.↗

A NICER View of the Massive Pulsar PSR J0740+6620 Informed by Radio Timing and XMM-Newton Spectroscopy

We report on Bayesian estimation of the radius, mass, and hot surface regions of the massive millisecond pulsar PSR J0740+6620, conditional on pulse-profile modeling of Neutron Star Interior Composition Explorer X-ray Timing Instrument event data. We condition on informative pulsar mass, distance, and orbital inclination priors derived from the joint North American Nanohertz Observatory for Gravitational Waves and Canadian Hydrogen Intensity Mapping Experiment/Pulsar wideband radio timing measurements of Fonseca et al. We use XMM-Newton European Photon Imaging Camera spectroscopic event data to inform our X-ray likelihood function. The prior support of the pulsar radius is truncated at 16 km to ensure coverage of current dense matter models. We assume conservative priors on instrument calibration uncertainty. We constrain the equatorial radius and mass of PSR J0740+6620 to be-+12.390.981.30km and-+2.0720.0660.067Me respectively, each reported as the posterior credible interval bounded by the 16% and 84% quantiles, conditional on surface hot regions that are non-overlapping spherical caps of fully ionized hydrogen atmosphere with uniform effective temperature; a posteriori, the temperature is=-+TlogK5.99100.060.05([])for each hot region. All software for the X-ray modeling framework is open-source and all data, model, and sample information is publicly available, including analysis notebooks and model modules in the Python language. Our marginal likelihood function of mass and equatorial radius is proportional to the marginal joint posterior density of those parameters(within the prior support)and can thus be computed from the posterior samples.

Millisecond pulsars↗

Energy Efficient Engine exhaust mixer model technology report addendum; phase 3 test program

The Phase 3 exhaust mixer test program was conducted to explore the trends established during previous Phases 1 and 2. Combinations of mixer design parameters were tested. Phase 3 testing showed that the best performance achievable within tailpipe length and diameter constraints is 2.55 percent better than an optimized separate flow base line. A reduced penetration design achieved about the same overall performance level at a substantially lower level of excess pressure loss but with a small reduction in mixing. To improve reliability of the data, the hot and cold flow thrust coefficient analysis used in Phases 1 and 2 was augmented by calculating percent mixing from traverse data. Relative change in percent mixing between configurations was determined from thrust and flow coefficient increments. The calculation procedure developed was found to be a useful tool in assessing mixer performance. Detailed flow field data were obtained to facilitate calibration of computer codes.

Larkin, M. J.↗