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DOE OSTI2020

Evaluation of the Four-Dimensional Ensemble-Variational Hybrid Data Assimilation with Self-Consistent Regional Background Error Covariance for Improved Hurricane Intensity Forecasts

The feasibility of a hurricane initialization framework based on the Gridpoint Statistical Interpolation (GSI)-based four-dimensional ensemble-variational (GSI-4DEnVar) hybrid data assimilation system for the Hurricane Weather Research and Forecasting model (HWRF) model is evaluated in this study. The system considers the temporal evolution of error covariances via the use of four-dimensional ensemble perturbations that are provided by high-resolution, self-consistent HWRF ensemble forecasts. It is different from the configuration of the GSI-based three-dimensional ensemble-variational (GSI-3DEnVar) hybrid data assimilation system, similar to that used in the operational HWRF, which employs background error covariances provided by coarser-resolution global ensembles from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) ensemble Kalman filtering data assimilation system. In addition, our proposed initialization framework discards the empirical intensity correction in the vortex initialization package that is employed by the GSI-3DEnVar initialization framework in operational HWRF. Data assimilation and numerical simulation experiments for Hurricanes Joaquin (2015), Patricia (2015), and Matthew (2016) are conducted during their intensity changes. The impacts of two initialization frameworks on the HWRF analyses and forecasts are compared. It is found that GSI-4DEnVar leads to a reduction in track, minimum sea level pressure (MSLP), and maximum surface wind (MSW) forecast errors in all of the HWRF simulations, compared with the GSI-3DEnVar initialization framework. With assimilating high-resolution observations within the hurricane inner-core region, GSI-4DEnVar can produce the initial hurricane intensity reasonably well without the empirical vortex intensity correction. Further diagnoses with Hurricane Joaquin indicate that GSI-4DEnVar can significantly alleviate the imbalances in the initial conditions and enhance the performance of the data assimilation and subsequent hurricane intensity and precipitation forecasts

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1984

Numerical simulations of the Ross Sea tides

Tidal currents below the floating Ross Ice shelf are reconstructed by using a numerical tidal model. They are predominantly diurnal, achieve maximum strength in regions near where the ice shelf runs aground, and are significantly enhanced by topographic Rossby wave propagation along the ice front. A comparison with observations of the vertical motion of the ice shelf surface indicates that the model reproduces the diurnal tidal characteristics within 20 percent. Similar agreement for the relatively weak semidiurnal tides was not obtained, and this calls attention to possible errors of the open boundary forcing obtained from global-ocean tidal simulations and to possible errors in mapping zones of ice shelf grounding. Air-sea contact below the ice shelf is eliminated by the thick ice cover. The dominant sub-ice-shelf circulation may thus be tidally induced. A preliminary assessment of sub-ice-shelf conditions based on the numerical tidal simulations suggests that (1) strong barotropic circulation is driven along the ice front and (2) tidal fronts may form in the sub-ice-shelf cavity where the water column is thin and where the buoyancy input is weak.

Macayeal, D. R.↗

DOE OSTI2020

CAKE: Consistent Automatic Kinetic Equilibrium reconstruction

Magnetohydrodynamic equilibrium reconstructions with kinetic constraints are an essential input of many tokamak stability and transport analysis work- flows. The reconstructions themselves also contain useful information about pressure and current density distributions within the plasma which can be used to drive other calculations. While standardized magnetic-only, and partially kinetic equilibrium reconstruction is widely available and used, re- constructions for well diagnosed machines such as DIII-D, that incorporates a large and heterogeneous set of internal diagnostic measurements yet robustly reaching high numerical accuracy have been a time intensive, manual process. The Consistent Automatic Kinetic Equilibrium reconstruction tool (CAKE) has been developed and implemented at DIII-D for producing low error, kinetically constrained reconstructions without human intervention, and to identify strategies for doing so that would be broadly applicable. Here, the techniques employed to allow CAKE to handle data of limited quality and availability, as well as the full automation of the workflow may assist future efforts to form kinetic constraint profiles in real time plasma control applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Comparing Sensor Fusion and Multimodal Chemometric Models for Monitoring U(VI) in Complex Environments Representative of Irradiated Nuclear Fuel

Optical sensors and chemometric models were leveraged for the quantification of uranium(VI) (0–100 μg mL –1 ), europium (0–150 μg mL –1 ), samarium (0–250 μg mL –1 ), praseodymium (0–350 μg mL –1 ), neodymium (0–1000 μg mL –1 ), and HNO 3 (2–4 M) with varying corrosion product (iron, nickel, and chromium) levels using laser fluorescence, Raman scattering, and ultraviolet–visible–near-infrared absorption spectra. In this paper, an efficient approach to developing and evaluating tens of thousands of partial least-squares regression (PLSR) models, built from fused optical spectra or multimodal acquisitions, is discussed. Each PLSR model was optimized with unique preprocessing combinations, and features were selected using genetic algorithm filters. The 7-factor D-optimal design training set contained just 55 samples to minimize the number of samples. The performance of PLSR models was evaluated by using an automated latent variable selection script. PLS1 regression models tailored to each species outperformed a global PLS2 model. PLS1 models built using fused spectra data and a multimodal (i.e., analyzed separately) approach yielded similar information, resulting in percent root-mean-square error of prediction values of 0.9–5.7% for the seven factors. Further, the optical techniques and data processing strategies established in this study allow for the direct analysis of numerous species without measuring luminescence lifetimes or relying on a standard addition approach, making it optimal for near-real-time, in situ measurements. Nuclear reactor modeling helped bound training set conditions and identified elemental ratios of lanthanide fission products to characterize the burnup of irradiated nuclear fuel. Leveraging fluorescence, spectrophotometry, experimental design, and chemometrics can enable the remote quantification and characterization of complex systems with numerous species, monitor system performance, help identify the source of materials, and enable rapid high-throughput experiments in a variety of industrial processes and fundamental studies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Automatic Differentiation in MetaPhysicL and Its Applications in MOOSE

Efficient solution via Newton’s method of nonlinear systems of equations requires an accurate representation of the Jacobian, corresponding to the derivatives of the component residual equations with respect to the degrees of freedom. In practice these systems of equations often arise from spatial discretization of partial differential equations used to model physical phenomena. These equations may involve domain motion or material equations that are complex functions of the systems’ degrees of freedom. Computing the Jacobian by hand in these situations is arduous and prone to error. Finite difference approximations of the Jacobian or its action are prone to truncation error, especially in multiphysics settings. Symbolic differentiation packages may be used, but often result in an excessive number of terms in realistic model scenarios. An alternative to symbolic and numerical differentiation is automatic differentiation (AD), which propagates derivatives with every elementary operation of a computer program, corresponding to continual application of the chain rule. Automatic differentiation offers the guarantee of an exact Jacobian at a relatively small overhead cost. In this work, we outline the adoption of AD in the Multiphysics Object Oriented Simulation Environment (MOOSE) via the MetaPhysicL package. We describe the application of MOOSE’s AD capability to several sets of physics that were previously infeasible to model via hand-coded or Jacobian-free simulation techniques, including arbitrary Lagrangian-Eulerian and level-set simulations of laser melt pools, phase-field simulations with free energies provided through neural networks, and metallic nuclear fuel simulations that require inner Newton loop calculation of nonlinear material properties.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Decentralized Filtering Adaptive Neural Network Control for Uncertain Switched Interconnected Nonlinear Systems

This article presents a novel decentralized filtering adaptive neural network control framework for uncertain switched interconnected nonlinear systems. Each subsystem has its own decentralized controller based on the established decentralized state predictor. For each subsystem, the nonlinear uncertainties are approximated by a Gaussian radial basis function (GRBF) neural network incorporated with a piecewise constant adaptive law, where the adaptive law will update adaptive parameters from the error dynamics between the host system and the decentralized state predictor by discarding the unknowns, whereas a decentralized filtering control law is derived to cancel both local and mismatched uncertainties from other subsystems, as well as achieve the local objective tracking of the host system. The achievement of global objective depends on the achievement of local objective for each subsystem. The matched uncertainties are canceled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. By exploiting the average dwell time principle, the error bounds between the real system and the virtual reference system, which defines the best performance that can be achieved by the closed-loop system, are derived. A numerical example is given to illustrate the effectiveness of the decentralized filtering adaptive neural network control architecture by comparing against the model reference adaptive control (MRAC).

Average dwell time, decentralized, filtering adapt↗

DOE OSTI2021

Machine-learning-aided cognitive reconfiguration for flexible-bandwidth HPC and data center networks [Invited]

This paper proposes a machine-learning (ML)-aided cognitive approach for effective bandwidth reconfiguration in optically interconnected datacenter/high-performance computing (HPC) systems. The proposed approach relies on a Hyper-X-like architecture augmented with flexible-bandwidth photonic interconnections at large scales using a hierarchical intra/inter-POD photonic switching layout. We first formulate the problem of the connectivity graph and routing scheme optimization as a mixed-integer linear programming model. A two-phase heuristic algorithm and a joint optimization approach are devised to solve the problem with low time complexity. Then, we propose an ML-based end-to-end performance estimator design to assist the network control plane with intelligent decision making for bandwidth reconfiguration. Numerical simulations using traffic distribution profiles extracted from HPC applications traces as well as random traffic matrices verify the accuracy performance of the ML design estimator ( < <#comment/> 9 % <#comment/> error) and demonstrate up to 5 × <#comment/> throughput gain from the proposed approach compared with the baseline Hyper-X network using fixed all-to-all intra/inter-portable data center interconnects.

Chen, Xiaoliang (ORCID:0000000278056237)↗

NASA NTRS1972

Space shuttle guidance, navigation and control equation document no. 4: Precision state and filter weighting matrix extrapolation

The Precision State and Filter Weighting Matrix Extrapolation Routine is described which provides the capability to extrapolate any spacecraft geocentric state vector either backwards or forwards in time through a force field consisting of the earth's primary central-force gravitational attraction and a superimposed perturbing acceleration. The routine also provides the capability of extrapolating the filter-weighting matrix along the precision trajectory. This matrix is a square root form of the error covariance matrix and contains statistical information relative to the accuracies of the state vectors and certain other optionally estimated quantities. The routine is a cooled algorithm for the numerical solution of modified forms of the basic differential equations which are satisfied by the geocentric state vector of the spacecraft's center of mass and by the filter-weighting matrix.

Robertson, W. M.↗

NASA NTRS1974

Remote temperature sounding in the presence of cloud by zenith scanning

The principles of remote sounding of vertical temperature profiles in planetary atmospheres containing cloud layers are presented for an approach that uses measurements at different angles to the local vertical to eliminate the unknown cloud effects. A numerical example for a model of the earth's atmosphere shows that soundings separated by 40 deg in zenith angle permit the recovery of the temperature profile with an error that is not significantly greater than that obtained in the clear atmosphere case, and without serious horizontal smear. It is proposed that the method will be valuable for the interpretation of measurements made by instruments on spin-stabilized spacecraft on planetary missions, since in these cases the required angular coverage is obtained automatically for most trajectories.

Taylor, F. W.↗

NASA NTRS1976

An algorithm for the weighting matrices in the sampled-data optimal linear regulator problem

The sampled-data optimal linear regulator problem provides a means whereby a control designer can use an understanding of continuous optimal regulator design to produce a digital state variable feedback control law which satisfies continuous system performance specifications. A basic difficulty in applying the sampled-data regulator theory is the requirement that certain digital performance index weighting matrices, expressed as complicated functions of system matrices, be computed. Infinite series representations are presented for the weighting matrices of the time-invariant version of the optimal linear sampled-data regulator problem. Error bounds are given for estimating the effect of truncating the series expressions after a finite number of terms, and a method is described for their computer implementation. A numerical example is given to illustrate the results.

Armstrong, E. S.↗

NASA NTRS1981

Rapid inversion of limb radiance data using an emissivity growth approximation

The time-consuming nature of limb relaxation-type inversion algorithms is due primarily to the numerous integrations over an absorption band to obtain forward radiance values with which to compare measured values. A new method has been devised for the quick and accurate (0.5% error) calculation of single gas broadband (approximately 100 per cm) limb radiance. The method uses a precalculated data base consisting of homogeneous path emissivity vs mass path data for a wide range of temperature and pressure. A 50-km altitude range, 1-km resolution, constituent inversion employing this method requires under 1 sec of computational time when run on modern computer hardware. The method does not rely upon a priori statistical knowledge.

Gordley, L. L.↗

NASA NTRS1987

Computational procedures for evaluating the sensitivity derivatives of vibration frequencies and Eigenmodes of framed structures

Computational procedures are presented for evaluating the sensitivity derivatives of the vibration frequencies and eigenmodes of framed structures. Both a displacement and a mixed formulation are used. The two key elements of the computational procedure are: (a) Use of dynamic reduction techniques to substantially reduce the number of degrees of freedom; and (b) Application of iterative techniques to improve the accuracy of the derivatives of the eigenmodes. The two reduction techniques considered are the static condensation and a generalized dynamic reduction technique. Error norms are introduced to assess the accuracy of the eigenvalue and eigenvector derivatives obtained by the reduction techniques. The effectiveness of the methods presented is demonstrated by three numerical examples.

Fetterman, Timothy L.↗

NASA NTRS1988

The effect of the solenoidal condition on the numerical magnetohydrodynamic simulation of coronal dynamics

Several MHD simulations of coronal dynamics performed more than 10 years ago violated the solenoidality condition for an 'open' magnetic field topology. Using an improved code, consideration is given to the effect on the physical validity of the numerical simulation (for a representative pulse disturbance) for the case when solenoidality is deliberately violated as compared to the case when it is preserved. It is found that the error incurred in this specific case ('open' topology) in the energy density and in the plasma density profiles is rather small and, hence, does not invalidate the earlier conclusions concerning mass and wave motion.

Wu, S. T.↗

NASA NTRS1992

A numerical investigation of hydrogen combustion in Mach 2 flow

A numerical study is conducted of a reacting flowfield generated by a single hydrogen jet injected transversely behind a rearward facing step. A nonreacting mixing study was followed by a reacting simulation. The computation simulates a current experimental condition. The validation of the numerical solution was limited to a comparison of the wall-pressure distribution along the wall. The comparison indicates agreement between the experiment and the prediction with a maximum error of 7 percent. The addition of the reaction responsible for HO2 production (H + O2 + M = HO2 + M) to an initially simplified chemical mechanism reduced the exponential growth of the free radicals and reduced the amount of heat released by combustion; as a result, the flowfield was significantly changed. A reversed flow was obtained in limited regions of the flow.

Segal, Corin↗

NASA NTRS1992

Line-of-sight control of the CSI evolutionary model - mu control

The design, analysis, and simulation of a control law that guarantees a fine pointing performance under external disturbances and model uncertainties are investigated. The authors examine the achievable performance and modeling errors for the control-structure interaction (CSI) evolutionary model structure and highlight the importance of accurate knowledge of structural frequencies and damping values for very lightly damped structures. Numerical results indicate that a limited but significant line-of-sight pointing performance robustness can be attained in spite of modeled structured and unstructured uncertainties in the system. The simulation results reported demonstrate typical performance levels, types of uncertainties and their magnitudes, and design tradeoffs for a realistic laboratory model of a large flexible space structure.

Lim, K. B.↗

NASA NTRS1996

Multidisciplinary Design Of Hot Composite Structures

Unified computer code developed to implement multidisciplinary approach to design and analysis of composite-material structures that must withstand high temperatures. Code modular: includes executive module communicating with and coordinating other modules performing calculations pertaining to traditionally separate disciplines like those of acoustics, structural vibrations, structural loads, and thermal effects. Essential feature, finite-element numerical simulation of relevant physical phenomena according to applicable disciplines. Same finite-element mesh used in thermal, vibrational, and structural analyses; minimizing data-preparation time and eliminating errors incurred in transforming temperatures from one finite-element mesh to another.

Chamis, Christos C.↗

NASA NTRS1999

The Sunyaev-Zel'dovich Effect in Abell 370

We present interferometric measurements of the Sunyaev-Zel'dovich (SZ) effect towards the galaxy cluster Abell 370. These measurements, which directly probe the pressure of the cluster's gas, show the gas is strongly aspherical, on agreement with the morphology revealed by x-ray and gravitational lensing observations. We calculate the cluster's gas mass fraction by comparing the gas mass derived from the SZ measurements to the lensing-derived gravitational mass near the critical lensing radius. We also calculate the gas mass fraction from the SZ data by deriving the total mass under the assumption that the gas is in hydrostatic equilibrium (HSE). We test the assumptions in the HSE method by comparing the total cluster mass implied by the two methods. The Hubble constant derived for this cluster, when the known systematic uncertainties are included, has a very wide range of values and therefore does not provide additional constraints on the validity of the assumptions. We examine carefully the possible systematic errors in the gas fraction measurement. The gas fraction is a lower limit to the cluster's baryon fraction and so we compare the gas mass fraction, calibrated by numerical simulations to approximately the virial radius, to measurements of the global mass fraction of baryonic matter, OMEGA(sub B)/OMEGA(sub matter). Our lower limit to the cluster baryon fraction is f(sub B) = (0.043 +/- 0.014)/h (sub 100). From this, we derive an upper limit to the universal matter density, OMEGA(sub matter) <= 0.72/h(sub 100), and a likely value of OMEGA(sub matter) <= (0.44(sup 0.15, sub -0.12)/h(sub 100).

Grego, Laura↗

NASA NTRS2004

Hyper-X Post-Flight Trajectory Reconstruction

This paper discusses the formulation and development of a trajectory reconstruction tool for the NASA X{43A/Hyper{X high speed research vehicle, and its implementation for the reconstruction and analysis of ight test data. Extended Kalman ltering techniques are employed to reconstruct the trajectory of the vehicle, based upon numerical integration of inertial measurement data along with redundant measurements of the vehicle state. The equations of motion are formulated in order to include the effects of several systematic error sources, whose values may also be estimated by the ltering routines. Additionally, smoothing algorithms have been implemented in which the nal value of the state (or an augmented state that includes other systematic error parameters to be estimated) and covariance are propagated back to the initial time to generate the best-estimated trajectory, based upon all available data. The methods are applied to the problem of reconstructing the trajectory of the Hyper-X vehicle from ight data.

Karlgaard, Christopher D.↗