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At least 613 records · Page 34

Physics-Based Approach to Predict the Solar Activity Cycles

Observations of the complex highly non-linear dynamics of global turbulent flows and magnetic fields are currently available only from Earth-side observations. Recent progress in helioseismology has provided us some additional information about the subsurface dynamics, but its relation to the magnetic field evolution is not yet understood. These limitations cause uncertainties that are difficult take into account, and perform proper calibration of dynamo models. The current dynamo models have also uncertainties due to the complicated turbulent physics of magnetic field generation, transport and dissipation. Because of the uncertainties in both observations and theory, the data assimilation approach is natural way for the solar cycle prediction and estimating uncertainties of this prediction. I will discuss the prediction results for the upcoming Solar Cycle 25 and their uncertainties and affect of Ensemble Kalman Filter parameters to resulting predictions.

Physics-Based↗

Assimilation of satellite microwave observations over the rainbands of tropical cyclones

A novel Bayesian Monte Carlo integration (BMCI) technique was developed to retrieve geophysical variables from satellite microwave radiometer data in the presence of tropical cyclones. The BMCI technique includes three steps: generating a stochastic database, simulating satellite brightness temperatures using a radiative transfer model, and retrieving geophysical variables such as profiles of temperature, relative humidity, and cloud liquid and ice water content from real observations. The technique also provides uncertainty estimates for each retrieval and can output the error covariance matrix of selected parameters. The measurements from the Advanced Technology Microwave Sounder (ATMS) on board Suomi National Polar-Orbiting Partnership (Suomi NPP) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) were used as input. A new technique was developed to correct the ATMS and GMI observations for the beam-filling effect, which is due to small-scale variability of precipitation and clouds when compared with the instrument footprint and also the nonlinear relation between the brightness temperature and precipitation. In addition, the assimilation of the BMCI retrievals into the NASA GEOS model is discussed for Hurricane Maria. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns. Two possible factors that may limit the impact of the BMCI retrievals include 1) the resolution of the model (about 25 km), which was too coarse to show the potential of the BMCI data in improving the representation of tropical storms in the model forecast, and 2) the data assimilation system not being able to consider vertically correlated observation errors.

Isaac Moradi↗

A Procedure for Calculating the Vertical Space Height of the Sacrum When Determining Skeletal Height for Use in the Anatomical Method of Adult Stature Estimation

Abstract Estimating stature from skeletonized remains is one of the essential parameters in the development of a biological profile. A new procedure for determining skeletal height ( SKH ) incorporating the vertical space height ( VSH ) from the anterior margin of the sacral promontory to the superior margins of the acetabulae for use in the anatomical method of stature estimation is introduced. Regression equations for stature estimation were generated from measurements of 38 American males of European ancestry from the William M. Bass Donated Skeletal Collection. The modification to the procedure results in a SKH that is highly correlated with stature ( r = 0.925–0.948). Stature estimates have low standard errors of the estimate ranging from 21.79 to 25.95 mm, biases from to 0.50 to 0.94 mm, and accuracy rates from 17.71 mm to 19.45 mm. The procedure for determining the VSH , which replaces “S1 height” in traditional anatomical method models, is a key improvement to the method.

Hayashi, Atsuko↗

Market Assessment of Forward-Looking Turbulence Sensing Systems

This viewgraph presentation provides a cost benefit analysis of three next-generation forward-looking turbulence sensing systems: X band turbulence radar system for convective turbulence, LIDAR based turbulence systems to sense clear air turbulence and a combined hybrid system. Parameters for the cost benefit analysis were established using a business model which considered injury rates, cost of injuries, indirect costs, market penetration rate estimates and product success characteristics. Topics covered include: study approach, business case equations, data acquisition, benchmark analysis. Data interpretation from the cost benefit analysis is presented. The researchers conclude that the market potential for these products is based primarily on injury cost reduction and that X band radar systems have the greatest chance for commercial success.

Kauffmann, Paul↗

Search for an Exotic S=-2, Q=-2 Baryon Resonance in Proton-Proton Interactions at $\sqrt{s_{NN}}$ = 17.3 GeV

Searches and analyses of strong gravitational lenses are challenging due to the rarity and image complexity of these astronomical objects. Next-generation surveys (both ground- and space-based) will provide more opportunities to derive science from these objects, but only if they can be analyzed on realistic time-scales. Currently, these analyses are expensive. In this work, we present a regression analysis with uncertainty estimates using deep learning models to measure four parameters of strong gravitational lenses in simulated Dark Energy Survey data. Using only $gri$-band images, we predict Einstein Radius, lens velocity dispersion, lens redshift to within $10-15\%$ of truth values and source redshift to $30\%$ of truth values, along with predictive uncertainties. This work helps to take a step along the path of faster analyses of strong lenses with deep learning frameworks.

79 ASTRONOMY AND ASTROPHYSICS↗

Controls for space structures

Assembly and operation of large space structures (LSS) in orbit will require robot-assisted docking and berthing of partially-assembled structures. These operations require new solutions to the problems of controls. This is true because of large transient and persistent disturbances, controller-structure interaction with unmodeled modes, poorly known structure parameters, slow actuator/sensor dynamical behavior, and excitation of nonlinear structure vibrations during control and assembly. For on-orbit assembly, controllers must start with finite element models of LSS and adapt on line to the best operating points, without compromising stability. This is not easy to do, since there are often unmodeled dynamic interactions between the controller and the structure. The indirect adaptive controllers are based on parameter estimation. Due to the large number of modes in LSS, this approach leads to very high-order control schemes with consequent poor stability and performance. In contrast, direct model reference adaptive controllers operate to force the LSS to track the desirable behavior of a chosen model. These schemes produce simple control algorithms which are easy to implement on line. One problem with their use for LSS has been that the model must be the same dimension as the LSS - i.e., quite large. A control theory based on the command generator tracker (CGT) ideas of Sobel, Mabins, Kaufman and Wen, Balas to obtain very low-order models based on adaptive algorithms was developed. Closed-loop stability for both finite element models and distributed parameter models of LSS was proved. In addition, successful numerical simulations on several LSS databases were obtained. An adaptive controller based on our theory was also implemented on a flexible robotic manipulator at Martin Marietta Astronautics. Computation schemes for controller-structure interaction with unmodeled modes, the residual mode filters or RMF, were developed. The RMF theory was modified to compensate slow actuator/sensor dynamics. These new ideas are being applied to LSS simulations to demonstrate the ease with which one can incorporate slow actuator/sensor effects into our design. It was also shown that residual mode filter compensation can be modified for small nonlinearities to produce exponentially stable closed-loop control. A theory for disturbance accommodating controllers based on reduced order models of structures was developed, and stability results for these controllers in closed-loop with large-scale finite element models of structures were obtained.

Balas, Mark↗

Efficient Signal Processing in BOTDA: Utilizing PCA and PCA-Based Neural Networks for Temperature Monitoring

This work presents a comparative analysis of the various signal processing techniques used in the Brillouin gain spectrum (BGS) peak estimation. Traditional fitting methods such as Lorentzian curve fitting (LCF) are slow and less effective in noisy data. PCA-based methods were tested on the experimental data: A Euclidian distance-based approach, and a probabilistic deep neural network (PDNN) based approach, both using 5 principal components to represent a single BGS. Both methods significantly reduce computational time with respect to LCF, whereas PDNN offers uncertainty insights along with the parameter value. Measuring a range of temperatures, analyzing accuracy, and speed, it can be concluded that PCA trained PDNN outperforms other methods, and appears to be helpful in scenario where large datasets are generated.

Brillouin optical time domain analysis↗

Measuring the thermal and ionization state of the low- z IGM using likelihood free inference

ABSTRACT We present a new approach to measure the power-law temperature density relationship $T=T_0 (\rho/ \bar{\rho })^{\gamma -1}$ and the UV background photoionization rate $\Gamma _{{{{\rm H\, {\small I}}}}{}}$ of the intergalactic medium (IGM) based on the Voigt profile decomposition of the Ly α forest into a set of discrete absorption lines with Doppler parameter b and the neutral hydrogen column density $N_{\rm H\, {\small I}}$. Previous work demonstrated that the shape of the $b-N_{{{{\rm H\, {\small I}}}}{}}$ distribution is sensitive to the IGM thermal parameters T0 and γ, whereas our new inference algorithm also takes into account the normalization of the distribution, i.e. the line-density dN/dz, and we demonstrate that precise constraints can also be obtained on $\Gamma _{{{{\rm H\, {\small I}}}}{}}$. We use density-estimation likelihood-free inference (DELFI) to emulate the dependence of the $b-N_{{{{\rm H\, {\small I}}}}{}}$ distribution on IGM parameters trained on an ensemble of 624 nyx hydrodynamical simulations at z = 0.1, which we combine with a Gaussian process emulator of the normalization. To demonstrate the efficacy of this approach, we generate hundreds of realizations of realistic mock HST/COS data sets, each comprising 34 quasar sightlines, and forward model the noise and resolution to match the real data. We use this large ensemble of mocks to extensively test our inference and empirically demonstrate that our posterior distributions are robust. Our analysis shows that by applying our new approach to existing Ly α forest spectra at z ≃ 0.1, one can measure the thermal and ionization state of the IGM with very high precision ($\sigma _{\log T_0} \sim 0.08$ dex, σγ ∼ 0.06, and $\sigma _{\log \Gamma _{{{{\rm H\, {\small I}}}}{}}} \sim 0.07$ dex).

79 ASTRONOMY AND ASTROPHYSICS↗

Solar neutrino detection in liquid xenon detectors via charged-current scattering to excited states

We investigate the prospects for real-time detection of solar neutrinos via the charged-current neutrino-nucleus scattering process in liquid xenon time projection chambers. We use a nuclear shell model, benchmarked with experimental data, to calculate the cross sections for populating specific excited states of the cesium nuclei produced by neutrino capture on Xe 131 and Xe 136 . The shell model is further used to compute the decay schemes of the low-lying 1 + excited states of Cs 136 , for which there is sparse experimental data. We explore the possibility of tagging the characteristic deexcitation γ rays/conversion electrons using two techniques: spatial separation of their energy deposits using event topology and their time separation using delayed coincidence. The efficiencies in each case are evaluated within a range of realistic detector parameters. We find that the topological signatures are likely to be dominated by radon backgrounds, but that a delayed-coincidence signature from long-lived states predicted in Cs 136 may enable background-free detection of CNO neutrino interactions in next-generation experiments with smaller uncertainty than current measurements. We also estimate the sensitivity as a function of exposure for detecting the solar-temperature-induced line shift in Be 7 neutrino emission, which may provide a new test of solar models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Modal-Parameter Extraction Procedure

Procedure accommodates multiple input excitations. Improved modalparameter extraction procedure applicable to linear, time-invariant systems derived in 92-page report. Algorithm allows multiple noncoherent input excitations applied to structure and generates consistent set of modal parameters. Procedure extension of simultaneous frequency-domain (SFD) techniques achieved through investigation of two automatic methods for reducing effective problem size while minimizing amount of user interaction. In several sample runs, independentcoordinate reduction method shown more accurate method for small sample size. Principle-component method used to estimate number of modes active in given frequency range.

Kurdila, A. H.↗

Symbolic enhancement of perspective displays

Two exocentric azimuth judgment experiments with a perspective display were conducted with 16 subjects. Previous work has shown these judgments to exhibit a bias possibly due to misinterpretation of the viewing parameters used to generate the display. Though geometric compensations may be used to correct for the bias, an alternate technique selected in the following 2 experiments was the introduction of symbolic enhancements in the form of compass roses. It is suggested that a compass rose with 30 deg divisions results in overall optimal azimuth estimation accuracy when accuracy and decision time are both considered. The data also suggest that the added radial lines on the compass roses may interact with normalization processes that influence the judgment errors.

Ellis, Stephen R.↗

Airplane takeoff and landing performance monitoring system

The invention is a real-time takeoff and landing performance monitoring system for an aircraft which provides a pilot with graphic and metric information to assist in decisions related to achieving rotation speed (V.sub.R) within the safe zone of a runway, or stopping the aircraft on the runway after landing or take-off abort. The system processes information in two segments: a pretakeoff segment and a real-time segment. One-time inputs of ambient conditions and airplane configuration information are used in the pretakeoff segment to generate scheduled performance data. The real-time segment uses the scheduled performance data, runway length data and transducer measured parameters to monitor the performance of the airplane throughout the takeoff roll. Airplane and engine performance deficiencies are detected and annunciated. A novel and important feature of this segment is that it updates the estimated runway rolling friction coefficient. Airplane performance predictions also reflect changes in head wind occurring as the takeoff roll progresses. The system provides a head-down display and a head-up display. The head-up display is projected onto a partially reflective transparent surface through which the pilot views the runway. By comparing the present performance of the airplane with a predicted nominal performance based upon given conditions, performance deficiencies are detected by the system.

Middleton, David B.↗

Probabilistic Analysis of a Composite Crew Module

An approach for conducting reliability-based analysis (RBA) of a Composite Crew Module (CCM) is presented. The goal is to identify and quantify the benefits of probabilistic design methods for the CCM and future space vehicles. The coarse finite element model from a previous NASA Engineering and Safety Center (NESC) project is used as the baseline deterministic analysis model to evaluate the performance of the CCM using a strength-based failure index. The first step in the probabilistic analysis process is the determination of the uncertainty distributions for key parameters in the model. Analytical data from water landing simulations are used to develop an uncertainty distribution, but such data were unavailable for other load cases. The uncertainty distributions for the other load scale factors and the strength allowables are generated based on assumed coefficients of variation. Probability of first-ply failure is estimated using three methods: the first order reliability method (FORM), Monte Carlo simulation, and conditional sampling. Results for the three methods were consistent. The reliability is shown to be driven by first ply failure in one region of the CCM at the high altitude abort load set. The final predicted probability of failure is on the order of 10-11 due to the conservative nature of the factors of safety on the deterministic loads.

FROM↗

Solar Sail Torque Model Characterization for the Near Earth Asteroid Scout Mission

Near Earth Asteroid Scout (NEA Scout) was a mission to test solar sail propulsion for orbital transfer from cislunar space to flyby and image an asteroid. Had it succeeded, one of the mission goals was to characterize the solar torque on the sail to ensure successful attitude control for the orbit transfer and imaging the asteroid. The simulation used to develop the flight attitude control software uses the generalized model for solar sails, a tensor equation of the forces and torques on sails of arbitrary shape. Rios-Reyes and Scheeres developed a general process to update the torque tensor coefficients using estimates of sail torque over a range of directions to the sun. Their process was adapted and implemented for the specific case of NEA Scout using spacecraft telemetry collected during sail characterization maneuvers in combination with simulation models and parameters. The NEA Scout maneuvers were limited to the operating range of the mission and constraints of the control hardware and allowed safe testing of each attitude before proceeding to the next. The NEA Scout reaction wheel speeds are used to measure accumulated momentum, while the Active Mass Translator (AMT) position is used to subtract out the torque from the center of mass crossed with the sail force and isolate the torque from only the sail shape. The process was tested by running attitude control simulations of the characterization maneuvers, generating simulated telemetry, estimating the solar torques, then using a least squares estimating the solar torque coefficients using least-squares and then performing a least-squares fit to the solar torque tensor coefficients. These estimated coefficients were tested by evaluating the solar torques under the same conditions as the simulated telemetry and comparing to the true simulated torques. Solar force model updates can be performed separately by observing the effect of the sail on the trajectory, and the torque model can be refined using those solar force updates. This process met the needs of the NEA Scout mission and can be adapted to characterize the solar torque for other missions with different sails.

solar sail↗

Solar Sail Torque Model Characterization for the Near Earth Asteroid Scout Mission

Near Earth Asteroid Scout (NEA Scout) was a mission to test solar sail propulsion for orbital transfer from cislunar space to flyby and image an asteroid. One of the goals of the mission was to characterize the solar torque on the sail to ensure successful attitude control for the orbit transfer and imaging the asteroid. The simulation used to develop the flight attitude control software uses the generalized model for solar sails, a tensor equation of the forces and torques on sails of arbitrary shape. Rios-Reyes and Scheeres developed a general process to update the torque tensor coefficients using estimates of sail torque over a range of directions to the sun. Their process was adapted and implemented for the specific case of NEA Scout using spacecraft telemetry collected during sail characterization maneuvers in combination with simulation models and parameters. The NEA Scout maneuvers were limited to the operating range of the mission and constraints of the control hardware and allowed safe testing of each attitude before proceeding to the next. The NEA Scout reaction wheel speeds are used to measure accumulated momentum, while the Active Mass Translator (AMT) position is used to subtract out the torque from the center of mass crossed with the sail force and isolate the torque from only the sail shape. The process was tested by running attitude control simulations of the characterization maneuvers, generating simulated telemetry, estimating the solar torques, then using a least squares estimating the solar torque coefficients using least-squares and then performing a least-squares fit to the solar torque tensor coefficients. These estimated coefficients were tested by evaluating the solar torques under the same conditions as the simulated telemetry and comparing to the true simulated torques. Solar force model updates can be performed separately by observing the effect of the sail on the trajectory, and the torque model can be refined using those solar force updates. This process met the needs of the NEA Scout mission and can be adapted to characterize the solar torque for other missions with different sails.

solar sail↗

Photocatalytic Active Radiation Measurements and Use

Photocatalytic materials are being used to purify air, to kill microbes, and to keep surfaces clean. A wide variety of materials are being developed, many of which have different abilities to absorb various wavelengths of light. Material variability, combined with both spectral illumination intensity and spectral distribution variability, will produce a wide range of performance results. The proposed technology estimates photocatalytic active radiation (PcAR), a unit of radiation that normalizes the amount of light based on its spectral distribution and on the ability of the material to absorb that radiation. Photocatalytic reactions depend upon the number of electron-hole pairs generated at the photocatalytic surface. The number of electron-hole pairs produced depends on the number of photons per unit area per second striking the surface that can be absorbed and whose energy exceeds the bandgap of the photocatalytic material. A convenient parameter to describe the number of useful photons is the number of moles of photons striking the surface per unit area per second. The unit of micro-einsteins (or micromoles) of photons per m2 per sec is commonly used for photochemical and photoelectric-like phenomena. This type of parameter is used in photochemistry, such as in the conversion of light energy for photosynthesis. Photosynthetic response correlates with the number of photons rather than by energy because, in this photochemical process, each molecule is activated by the absorption of one photon. In photosynthesis, the number of photons absorbed in the 400 700 nm spectral range is estimated and is referred to as photosynthetic active radiation (PAR). PAR is defined in terms of the photosynthetic photon flux density measured in micro-einsteins of photons per m2 per sec. PcAR is an equivalent, similarly modeled parameter that has been defined for the photocatalytic processes. Two methods to measure the PcAR level are being proposed. In the first method, a calibrated spectrometer with a cosine receptor is used to measure the spectral irradiance. This measurement, in conjunction with the photocatalytic response as a function of wavelength, is used to estimate the PcAR. The photocatalytic response function is determined by measuring photocatalytic reactivity as a function of wavelength. In the second method, simple shaped photocatalytic response functions can be simulated with a broad-band detector with a cosine receptor appropriately filtered to represent the spectral response of the photocatalytic material. This second method can be less expensive than using a calibrated spectrometer.

Davis, Bruce A.↗

Dark Energy Survey Year 3 results: Simulation-based 𝑤CDM inference from weak lensing and galaxy clustering maps with deep learning: Analysis design

Data-driven approaches using deep learning are emerging as powerful techniques to extract non-Gaussian information from cosmological large-scale structure. Here, this work presents the first simulation-based inference (SBI) pipeline that combines weak lensing and galaxy clustering maps in a realistic Dark Energy Survey Year 3 (DES Y3) configuration and serves as preparation for a forthcoming analysis of the survey data. We develop a scalable forward model based on the CosmoGridV1 suite of N-body simulations to generate over one million self-consistent mock realizations of DES Y3 at the map level. Leveraging this large dataset, we train deep graph convolutional neural networks on the full survey footprint in spherical geometry to learn low-dimensional features that approximately maximize mutual information with target parameters. These learned compressions enable neural density estimation of the implicit likelihood via normalizing flows in a ten-dimensional parameter space spanning cosmological 𝑤CDM, intrinsic alignment, and linear galaxy bias parameters, while marginalizing over baryonic, photometric redshift, and shear bias nuisances. To ensure robustness, we extensively validate our inference pipeline using synthetic observations derived from both systematic contaminations in our forward model and independent Buzzard galaxy catalogs. Our forecasts yield significant improvements in cosmological parameter constraints, achieving 2−3× higher figures of merit in the 𝛺 𝑚 − 𝑆 8 plane relative to our implementation of baseline two-point statistics and effectively breaking parameter degeneracies through probe combination. These results demonstrate the potential of SBI analyses powered by deep learning for upcoming Stage-IV wide-field imaging surveys.

Thomsen, A. [Zurich, ETH] (ORCID:0000000203099021)↗

Simulated Wake Characteristics Data for Closely Spaced Parallel Runway Operations Analysis

A simulation experiment was performed to generate and compile wake characteristics data relevant to the evaluation and feasibility analysis of closely spaced parallel runway (CSPR) operational concepts. While the experiment in this work is not tailored to any particular operational concept, the generated data applies to the broader class of CSPR concepts, where a trailing aircraft on a CSPR approach is required to stay ahead of the wake vortices generated by a lead aircraft on an adjacent CSPR. Data for wake age, circulation strength, and wake altitude change, at various lateral offset distances from the wake-generating lead aircraft approach path were compiled for a set of nine aircraft spanning the full range of FAA and ICAO wake classifications. A total of 54 scenarios were simulated to generate data related to key parameters that determine wake behavior. Of particular interest are wake age characteristics that can be used to evaluate both time- and distance- based in-trail separation concepts for all aircraft wake-class combinations. A simple first-order difference model was developed to enable the computation of wake parameter estimates for aircraft models having weight, wingspan and speed characteristics similar to those of the nine aircraft modeled in this work.

Guerreiro, Nelson M.↗