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NASA NTRS2007

NASA Langley's Approach to the Sandia's Structural Dynamics Challenge Problem

The objective of this challenge is to develop a data-based probabilistic model of uncertainty to predict the behavior of subsystems (payloads) by themselves and while coupled to a primary (target) system. Although this type of analysis is routinely performed and representative of issues faced in real-world system design and integration, there are still several key technical challenges that must be addressed when analyzing uncertain interconnected systems. For example, one key technical challenge is related to the fact that there is limited data on target configurations. Moreover, it is typical to have multiple data sets from experiments conducted at the subsystem level, but often samples sizes are not sufficient to compute high confidence statistics. In this challenge problem additional constraints are placed as ground rules for the participants. One such rule is that mathematical models of the subsystem are limited to linear approximations of the nonlinear physics of the problem at hand. Also, participants are constrained to use these models and the multiple data sets to make predictions about the target system response under completely different input conditions. Our approach involved initially the screening of several different methods. Three of the ones considered are presented herein. The first one is based on the transformation of the modal data to an orthogonal space where the mean and covariance of the data are matched by the model. The other two approaches worked solutions in physical space where the uncertain parameter set is made of masses, stiffnesses and damping coefficients; one matches confidence intervals of low order moments of the statistics via optimization while the second one uses a Kernel density estimation approach. The paper will touch on all the approaches, lessons learned, validation 1 metrics and their comparison, data quantity restriction, and assumptions/limitations of each approach. Keywords: Probabilistic modeling, model validation, uncertainty quantification, kernel density

Horta, Lucas G.↗

NASA NTRS2006

Proteomic Retrieval from Nucleic Acid Depleted Space-Flown Human Cells

Compared to experiments utilizing humans in microgravity, cell-based approaches to questions about subsystems of the human system afford multiple advantages, such as crew safety and the ability to achieve statistical significance. To maximize the science return from flight samples, an optimized method was developed to recover protein from samples depleted of nucleic acid. This technique allows multiple analyses on a single cellular sample and when applied to future cellular investigations could accelerate solutions to significant biomedical barriers to human space exploration. Cell cultures grown in American Fluoroseal bags were treated with an RNA stabilizing agent (RNAlater - Ambion), which enabled both RNA and immunoreactive protein analyses. RNA was purified using an RNAqueous(registered TradeMark) kit (Ambion) and the remaining RNA free supernatant was precipitated with 5% trichloroacetic acid. The precipitate was dissolved in SDS running buffer and tested for protein content using a bicinchoninic acid assay (1) (Sigma). Equal loads of protein were placed on SDS-PAGE gels and either stained with CyproOrange (Amersham) or transferred using Western Blotting techniques (2,3,4). Protein recovered from RNAlater-treated cells and stained with protein stain, was measured using Imagequant volume measurements for rectangles of equal size. BSA treated in this way gave quantitative data over the protein range used (Fig 1). Human renal cortical epithelial (HRCE) cells (5,6,7) grown onboard the International Space Station (ISS) during Increment 3 and in ground control cultures exhibited similar immunoreactivity profiles for antibodies to the Vitamin D receptor (VDR) (Fig 2), the beta isoform of protein kinase C (PKC ) (Fig 3), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (Fig 4). Parallel immunohistochemical studies on formalin-fixed flight and ground control cultures also showed positive immunostaining for VDR and other biomarkers (Fig 5). These results are consistent with data from additional antigenic recovery experiments performed on human Mullerian tumor cells cultured in microgravity (8).

Hammond, D. K.↗

DOE OSTI2018

Effects of Magnetic and Electric Field Uniformity on Coded Aperture Imaging Quality in a Cycloidal Mass Analyzer

Cycloidal mass analyzers are unique sector mass analyzers as they exhibit perfect double focusing, making them ideal for incorporating spatial aperture coding, which can increase the throughput of a mass analyzer without affecting the resolving power. However, the focusing properties of the cycloidal mass analyzer depend on the uniformity of the electric and magnetic fields. In this paper, finite element simulation and charged particle tracing were used to investigate the effect of field uniformity on imaging performance of a cycloidal mass analyzer. For the magnetic field, we evaluate a new permanent magnet geometry by comparing it to a traditional geometry. Results indicate that creating an aperture image in a cycloidal mass spectrometer with the same FWHM as the slit requires less than 1% variation in magnetic field strength along the ion trajectories. The new magnet design, called the opposed dipole magnet, has less than 1% field variation over an area approximately 62 × 65 mm; nearly twice the area available in a traditional design of similar size and weight. This allows ion imaging across larger detector arrays without loss of resolving power. In addition, we compare the aperture imaging quality of a traditionally used cycloidal mass spectrometer electric design with a new optimized design with improved field uniformity. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1995

Automatic differentiation evaluated as a tool for rotorcraft design and optimization

This paper investigates the use of automatic differentiation (AD) as a means for generating sensitivity analyses in rotorcraft design and optimization. This technique transforms an existing computer program into a new program that performs sensitivity analysis in addition to the original analysis. The original FORTRAN program calculates a set of dependent (output) variables from a set of independent (input) variables, the new FORTRAN program calculates the partial derivatives of the dependent variables with respect to the independent variables. The AD technique is a systematic implementation of the chain rule of differentiation, this method produces derivatives to machine accuracy at a cost that is comparable with that of finite-differencing methods. For this study, an analysis code that consists of the Langley-developed hover analysis HOVT, the comprehensive rotor analysis CAMRAD/JA, and associated preprocessors is processed through the AD preprocessor ADIFOR 2.0. The resulting derivatives are compared with derivatives obtained from finite-differencing techniques. The derivatives obtained with ADIFOR 2.0 are exact within machine accuracy and do not depend on the selection of step-size, as are the derivatives obtained with finite-differencing techniques.

Walsh, Joanne L.↗

DOE OSTI2020

Detection Limits and Near‐Field Ground Motions of Fast and Slow Earthquakes

Abstract We investigate theoretical limits to detection of fast and slow seismic events, and spatial variations of ground motion expected from M 6 earthquakes at short epicentral distances. The analyses are based on synthetic velocity seismograms calculated with the discrete wavenumber method assuming seismic velocities and attenuation properties of the crust in Southern California. The examined source properties include different magnitudes ( M −1.0 to M 6.0), static stress drops (0.1–10 MPa), and slow and fast ruptures (0.1–0.9 of shear wave velocity). For the M 6 events we also consider variations in rise times producing crack‐ and pulse‐type events and different rupture directivities. Slow events produce ground motion with considerably lower amplitude than corresponding regular fast earthquakes with the same magnitude, and hence are significantly more difficult to detect. The static stress drop and slip rise time also affect the maximum radiated seismic motion, and hence event detectability. Apart from geometrical factors, the saturation and depletion of seismic ground motion at short epicentral distances stem from radiation pattern, earthquake size (magnitude, stress drop), and rupture directivity. The rupture velocity, rise time, and directivity affect significantly the spatial pattern of the ground motions. The results can help optimizing detection of slow and fast small earthquakes and understand the spatial distribution of ground motion generated by large events.

58 GEOSCIENCES↗

DOE OSTI2023

A greedy Galerkin method to efficiently select sensors for linear dynamical systems

A key challenge in inverse problems is the selection of sensors to gather the most effective data. In this paper, we consider the problem of inferring the initial condition to a linear dynamical system and develop an efficient control-theoretical approach for greedily selecting sensors. Our method employs a Galerkin projection to reduce the size of the inverse problem, resulting in a computationally efficient algorithm for sensor selection. As a byproduct of our algorithm, we obtain a preconditioner for the inverse problem that enables the rapid recovery of the initial condition. Here, we analyze the theoretical performance of our greedy sensor selection algorithm as well as the performance of the associated preconditioner. Finally, we verify our theoretical results on various inverse problems involving partial differential equations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Nanodiamonds in Advancing Biomedical Sciences

Nanodiamonds (NDs), tetrahedral carbon frameworks with size ranging from 1 to 100 nanometers, have gained growing attention in recent years due to their distinct optical, thermal, and mechanical properties compared to other carbon nanomaterials (e.g., graphene, carbon nanotubes, carbon dots). Combined with a high surface-to-volume ratio and tunable and chemically versatile surfaces, these support broad applications across catalysis, electronics, and life sciences. Moreover, the biocompatible characteristics of NDs enable their controllable interfacial interactions with biological systems, positioning them as excellent candidates for advancing cutting-edge biomedical sciences, particularly through the engineering of efficient material-biointerfaces that facilitate optimal interactions with biological systems. Among various forms of NDs, fluorescent nanodiamonds (FNDs) have emerged as some of the most impactful and rapidly advancing materials, demonstrating strong potential in ultrasensitive spin-enhanced bioimaging, high-precision biosensing, traceable drug delivery, and quantum-enabled biomedical technologies. This Perspective introduces the key principles underlying NDs and FNDs, including their structural properties, synthesis methods, and surface functionalization strategies. It also highlights emerging biomedical applications of NDs and FNDs, with particular emphasis on neurological disorders. Last, the article discusses current challenges in advancing NDs as a multifunctional platform for neural therapies with translational potential toward clinical trials.

36 MATERIALS SCIENCE↗

NASA NTRS2014

Extravehicular Activity Asteroid Exploration and Sample Collection Capability

NASA's Asteroid Redirect Crewed Mission (ARCM) is challenged with primary mission objectives of demonstrating deep space Extravehicular Activity (EVA) and tools, and obtaining asteroid samples to return to Earth for further study. Although the Modified Advanced Crew Escape Suit (MACES) is used for the EVAs, it has limited mobility which increases fatigue and decreases the crews' capability to perform EVA tasks. Furthermore, previous Shuttle and International Space Station (ISS) spacewalks have benefited from EVA interfaces which have been designed and manufactured on Earth. Rigid structurally mounted handrails, and tools with customized interfaces and restraints optimize EVA performance. For ARCM, some vehicle interfaces and tools can leverage heritage designs and experience. However, when the crew ventures onto an asteroid capture bag to explore the asteroid and collect rock samples, EVA complexity increases due to the uncertainty of the asteroid properties. The variability of rock size, shape and composition, as well as bunching of the fabric bag will complicate EVA translation, tool restraint and body stabilization. The unknown asteroid hardness and brittleness will complicate tool use. The rock surface will introduce added safety concerns for cut gloves and debris control. Feasible solutions to meet ARCM EVA objectives were identified using experience gained during Apollo, Shuttle, and ISS EVAs, terrestrial mountaineering practices, NASA Extreme Environment Mission Operations (NEEMO) 16 mission, and during Neutral Buoyancy Laboratory testing in the MACES suit. The proposed concept utilizes expandable booms and integrated features of the asteroid capture bag to position and restrain the crew at the asteroid worksite. These methods enable the capability to perform both finesse, and high load tasks necessary to collect samples for scientific characterization of the asteroid. This paper will explore the design trade space and options that were examined for EVA, the overall concept for the EVAs including translation paths and body restraint methods, potential tools used to extract the samples, design implications for the Asteroid Redirect Vehicle (ARV) for EVA, the results of early development testing of potential EVA tasks, and extensibility of the EVA architecture to NASA's exploration missions.

Scoville, Zebulon↗

DOE OSTI2022

Simulations of frustrated Ising Hamiltonians using quantum approximate optimization

Novel magnetic materials are important for future technological advances. Theoretical and numerical calculations of ground-state properties are essential in understanding these materials, however, computational complexity limits conventional methods for studying these states. Here we investigate an alternative approach to preparing materials ground states using the quantum approximate optimization algorithm (QAOA) on near-term quantum computers. We study classical Ising spin models on unit cells of square, Shastry-Sutherland and triangular lattices, with varying field amplitudes and couplings in the material Hamiltonian. We find relationships between the theoretical QAOA success probability and the structure of the ground state, indicating that only a modest number of measurements (≲100) are needed to find the ground state of our nine-spin Hamiltonians, even for parameters leading to frustrated magnetism. We further demonstrate the approach in calculations on a trapped-ion quantum computer and succeed in recovering each ground state of the Shastry-Sutherland unit cell with probabilities close to ideal theoretical values. The results demonstrate the viability of QAOA for materials ground state preparation in the frustrated Ising limit, giving important first steps towards larger sizes and more complex Hamiltonians where quantum computational advantage may prove essential in developing a systematic understanding of novel materials.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Design and Application of CSC-Roll for Heavy Reduction of the Bloom Continuous Casting Process

Center quality control is a key issue affecting large-section bloom production and product quality. The central convex roll could avoid the bloom side part and yield a high reduction amount, which benefit the implement of heavy reduction (HR) for bloom continuous casting process without upgrading the mechanical and hydraulic system of withdrawal and straightening machine. In this work, a curving surface convex roll (CSC-Roll), which could significantly improve bloom center quality, was designed by finite element simulation for a 360 mm × 450 mm #45 steel continuous casting bloom. The optimal roll surface shape of the CSC-Roll was determined based on an analysis of the distribution of the reduction amount in the bloom center and the strain of the bloom centerline and inner surface. The calculation results showed that the optimal size of the CSC-Roll was 200 mm in convex platform region length, 30 mm in convex platform region height, and 80 mm in gradient curvature region length. The bloom heat transfer and deformation behavior in the CSC-Roll reduction process were then analyzed. The results showed that in the CSC-Roll HR process, 61.71 pct of the reduction amount could be transmitted to the inner side of the porosity zone. Macrographs of the 360 mm × 450 mm #45 steel continuous casting bloom proved that the bloom center quality was significantly improved after CSC-Roll HR was applied.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Towards Highly Scalable Ab Initio Molecular Dynamics (AIMD) Simulations on the Intel Knights Landing Manycore Processor

The Ab Initio Molecular Dynamics (AIMD) method allows scientists to treat the dynamics of molecular and condensed phase systems while retaining a first-principles-based description of their interactions. This extremely important method has tremendous computational requirements, because the electronic Schr¨odinger equation, approximated using Kohn-Sham Density Functional Theory (DFT), is solved at every time step. With the advent of manycore architectures, application developers have a significant amount of processing power within each compute node that can only be exploited through massive parallelism. A compute intensive application such as AIMD forms a good candidate to leverage this processing power. In this paper, we focus on adding thread level parallelism to the plane wave DFT methodology implemented in NWChem. Through a careful optimization of tall-skinny matrix products, which are at the heart of the Lagrange multiplier and nonlocal pseudopotential kernels, as well as 3D FFTs, our OpenMP implementation delivers excellent strong scaling on the latest Intel Knights Landing (KNL) processor. We assess the efficiency of our Lagrange multiplier kernels by building a Roofline model of the platform, and verify that our implementation is close to the roofline for various problem sizes. Finally, we present strong scaling results on the complete AIMD simulation for a 64 water molecules test case, that scales up to all 68 cores of the Knights Landing processor.

Environmental Molecular Sciences Laboratory↗

NASA NTRS2003

Fabricating Composite-Material Structures Containing SMA Ribbons

An improved method of designing and fabricating laminated composite-material (matrix/fiber) structures containing embedded shape-memory-alloy (SMA) actuators has been devised. Structures made by this method have repeatable, predictable properties, and fabrication processes can readily be automated. Such structures, denoted as shape-memory-alloy hybrid composite (SMAHC) structures, have been investigated for their potential to satisfy requirements to control the shapes or thermoelastic responses of themselves or of other structures into which they might be incorporated, or to control noise and vibrations. Much of the prior work on SMAHC structures has involved the use SMA wires embedded within matrices or within sleeves through parent structures. The disadvantages of using SMA wires as the embedded actuators include (1) complexity of fabrication procedures because of the relatively large numbers of actuators usually needed; (2) sensitivity to actuator/ matrix interface flaws because voids can be of significant size, relative to wires; (3) relatively high rates of breakage of actuators during curing of matrix materials because of sensitivity to stress concentrations at mechanical restraints; and (4) difficulty of achieving desirable overall volume fractions of SMA wires when trying to optimize the integration of the wires by placing them in selected layers only.

Turner, Travis L.↗

DOE OSTI2025

Universal method for the optimization of HDC coating uniformity on non-planar, non-stationary substrates for inertial confinement fusion targets

The thickness uniformity of chemical vapor deposited (CVD) diamond coatings on non-planar, non-stationary substrates depends on both the intrinsic instantaneous coating thickness distribution (ICTD) of the coating conditions used and, if applicable, on the frequency of substrate reorientation. While important for many CVD diamond applications, the relative impact of the ICTD and substrate reorientation on the coating thickness uniformity has not been studied. In this work, we systematically investigate the effect of these factors for microwave-plasma chemical vapor deposition (MPCVD) of diamond (referred to as high density carbon (HDC) in the inertial confinement fusion (ICF) community) coatings on spherical, rolling substrates. This coating technique is used to fabricate capsules for ICF experiments, which require extreme coating uniformity with <0.3 % thickness variation (so-called Mode 1 or M1) to ensure symmetric compression of imploding targets. To extract the otherwise unobservable reorientation timescale (Δt), Monte Carlo simulations were performed using experimental ICTD data as input. This combined approach confirms scaling relationships between the substrate reorientation timescale as well as coating thickness and coating uniformity, as expected from a 3D random walk. Simulations confirm that M1 is Rayleigh-distributed and scales as (Δt) 1/2 , consistent with the randomization of two angles that determine orientation of a sphere. We also demonstrate that, under the conditions studied, Δt is the dominant factor in determining thickness uniformity while the intrinsic ICTD has minimal impact. Finally, experiments show that Δt can be affected by total batch size under constant agitation conditions due to space constraints that limit the capsule reorientation kinetics. In conclusion, this study highlights the utility of a combined experiment-simulation approach as a general methodology for understanding and improving coating uniformity on non-planar, non-stationary substrates.

Capsule↗

NASA NTRS2013

Transmission Electron Microscopy of Itokawa Regolith Grains

Introduction: In a remarkable engineering achievement, the JAXA space agency successfully recovered the Hayabusa space-craft in June 2010, following a non-optimal encounter and sur-face sampling mission to asteroid 25143 Itokawa. These are the first direct samples ever obtained and returned from the surface of an asteroid. The Hayabusa samples thus present a special op-portunity to directly investigate the evolution of asteroidal sur-faces, from the development of the regolith to the study of the effects of space weathering. Here we report on our preliminary TEM measurements on two Itokawa samples. Methods: We were allocated particles RA-QD02-0125 and RA-QD02-0211. Both particles were embedded in low viscosity epoxy and thin sections were prepared using ultramicrotomy. High resolution images and electron diffraction data were ob-tained using a JEOL 2500SE 200 kV field-emission scanning-transmission electron microscope. Quantitative maps and anal-yses were obtained using a Thermo thin-window energy-dispersive x-ray (EDX) spectrometer. Results: Both particles are olivine-rich (Fo70) with μm-sized inclusions of FeS and have microstructurally complex rims. Par-ticle RA-QD02-0125 is rounded and has numerous sub-μm grains attached to its surface including FeS, albite, olivine, and rare melt droplets. Solar flare tracks have not been observed, but the particle is surrounded by a continuous ~50 nm thick, stuctur-ally disordered rim that is compositionally similar to the core of the grain. One of the surface adhering grains is pyrrhotite show-ing a S-depleted rim (~8-10 nm thick) with nanophase Fe metal grains (<5 nm) decorating the outermost surface. The pyrrhotite displays a complex superstructure in its core that is absent in the S-depleted rim. Particle RA-QD02-0211 contains solar flare particle tracks (~2x109 cm-2) and shows a structurally disordered rim ~100 nm thick. The track density corresponds to a surface exposure of ~103-104 years based on the track production rate of [1]. The dis-ordered rim is nanocrystalline with minor amorphous material between crystalline domains. Quantitative element maps show the outermost ~10 nm of the disordered rim is Si-rich. Discussion and Conclusions: Both particles record the ef-fects of space weathering processes on Itokawa. Noguchi et al. [2] proposed that the disordered rims they observed on Itokawa particles largely result from solar wind radiation damage and we arrive at a similar conclusion for the two particles we analyzed. The microstructure of the S-depleted layer on the pyrrhotite grain in RA-QD02-0125 is similar to that observed in troilite irradiated with ~1018 4 kV He+ [3, 4]. Prolonged irradiation has also been shown to disorder pyrrhotite such that the superstructure reflec-tions are lost [5].

Keller, Lindsay P.↗

NASA NTRS2024

Global Sensitivity Analysis of Simulated Remote Sensing Polarimetric Observations Over Snow

This study presents a detailed theoretical assessment of the information content of passive polarimetric observations over snow scenes, using a global sensitivity analysis (GSA) method. Conventional sensitivity studies focus on varying a single parameter while keeping all other parameters fixed. In contrast, the GSA correctly addresses the covariance of state parameters across their entire parameter space, hence favoring a more correct interpretation of inversion algorithms and the optimal design of their state vectors. The forward simulations exploit a vector radiative transfer model to obtain the Stokes vector emerging at the top of the atmosphere for different solar zenith angles, when the bottom boundary consists of a vertically resolved snowpack of non-spherical grains. The presence of light-absorbing particulates (LAPs), either embedded in the snow or aloft in the atmosphere above in the form of aerosols, is also considered. The results are presented for a set of wavelengths spanning the visible (VIS), near-infrared (NIR), and shortwave infrared (SWIR) region of the spectrum. The GSA correctly captures the expected, high sensitivity of the reflectance to LAPs in the VIS–NIR and to grain size at different depths in the snowpack in the NIR–SWIR. With adequate viewing geometries, mono-angle measurements of total reflectance in the VIS–SWIR (akin to those of the Moderate Resolution Imaging Spectroradiometer, MODIS) resolve grain size in the top layer of the snowpack sufficiently well. The addition of multi-angle polarimetric observations in the VIS–NIR provides information on grain shape and microscale roughness. The simultaneous sensitivity in the VIS–NIR to both aerosols and snow-embedded impurities can be disentangled by extending the spectral range to the SWIR, which contains information on aerosol optical depth while remaining essentially unaffected when the same particulates are mixed with the snow. Multi-angle polarimetric observations can therefore (i) effectively partition LAPs between the atmosphere and the surface, which represents a notorious challenge for snow remote sensing based on measurements of total reflectance only and (ii) lead to better estimates of grain shape and roughness and, in turn, the asymmetry parameter, which is critical for the determination of albedo. The retrieval uncertainties are minimized when the degree of linear polarization is used in place of the polarized reflectance. The Sobol indices, which are the main metric for the GSA, were used to select the state parameters in retrievals performed on data simulated for multiple instrument configurations. Improvements in retrieval quality with the addition of measurements of polarization, multi-angle views, and different spectral channels reflect the information content, identified by the Sobol indices, relative to each configuration. The results encourage the development of new remote sensing algorithms that fully leverage multi-angle and polarimetric capabilities of modern remote sensors. They can also aid flight planning activities, since the optimal exploitation of the information content of multi-angle measurements depends on the viewing geometry. The better characterization of surface and atmospheric parameters in snow-covered regions advances research opportunities for scientists of the cryosphere and ultimately benefits albedo estimates in climate models.

remote sensing↗

DOE OSTI2024

Medial axis and local thickness computation using the Fast Sweeping Method

This report describes an efficient and robust voxel-based methodology for computing the medial axis, local thickness, and distance-to-skeleton of arbitrary three-dimensional geometries. It is assumed that the object can be represented by an exact or approximate signed distance function on a discrete grid. The gradient of such function is used to formulate a hyperbolic partial differential equation (PDE) that models the collapse of the position vector in space. By exploiting the causality property of the PDE, the Fast Sweeping Method is able to obtain the solution in a finite number of sweeps independent of the mesh resolution. The intersection of characteristic lines leads to the formation of shocks and a discrete bisector function is used to identify the medial axis. The same PDE approach is used to compute the local thickness inside the object and obtain the distance-to-skeleton field. Multiple examples are given in two and three dimensions along with a resolution study. The methodology has optimal complexity and yields subsecond computational times for geometries with over a million zones on a single core. The methodology is also capable of parallelization across shared and distributed memory architectures.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems

Quantum computing is a computational paradigm with the potential to outperform classical methods for a variety of problems. Proposed recently, the Quantum Approximate Optimization Algorithm (QAOA) is considered as one of the leading candidates for demonstrating quantum advantage in the near term. QAOA is a variational hybrid quantum-classical algorithm for approximately solving combinatorial optimization problems. The quality of the solution obtained by QAOA for a given problem instance depends on the performance of the classical optimizer used to optimize the variational parameters. In this paper, we formulate the problem of finding optimal QAOA parameters as a learning task in which the knowledge gained from solving training instances can be leveraged to find high-quality solutions for unseen test instances. To this end, we develop two machine-learning-based approaches. Our first approach adopts a reinforcement learning (RL) framework to learn a policy network to optimize QAOA circuits. Our second approach adopts a kernel density estimation (KDE) technique to learn a generative model of optimal QAOA parameters. In both approaches, the training procedure is performed on small-sized problem instances that can be simulated on a classical computer; yet the learned RL policy and the generative model can be used to efficiently solve larger problems. Furthermore, extensive simulations using the IBM Qiskit Aer quantum circuit simulator demonstrate that our proposed RL- and KDE-based approaches reduce the optimality gap by factors up to 30.15 when compared with other commonly used off-the-shelf optimizers.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2009

Radar Differential Phase Signatures of Ice Orientation for the Prediction of Lightning Initiation and Cessation

The majority of lightning-related casualties typically occur during thunderstorm initiation (e.g., first flash) or dissipation (e.g., last flash). The physics of electrification and lightning production during thunderstorm initiation is fairly well understood. As such, the literature includes a number of studies presenting various radar techniques (using reflectivity and, if available, other dual-polarimetric parameters) for the anticipation of initial electrification and first lightning flash. These radar techniques have shown considerable skill at forecasting first flash. On the other hand, electrical processes and lightning production during thunderstorm dissipation are not nearly as well understood and few, if any, successful techniques have been developed to anticipate the last flash and subsequent cessation of lightning. One promising approach involves the use of dual-polarimetric radar variables to infer the presence of oriented ice crystals in lightning producing storms. In the absence of strong vertical electric fields, ice crystals fall with their largest (semi-major) axis in the horizontal associated with gravitational and aerodynamic forces. In thunderstorms, strong vertical electric fields (100-200 kV m(sup -1)) have been shown to orient small (less than 2 mm) ice crystals such that their semi-major axis is vertical (or nearly vertical). After a lightning flash, the electric field is typically relaxed and prior radar research suggests that ice crystals rapidly resume their preferred horizontal orientation. In active thunderstorms, the vertical electric field quickly recovers and the ice crystals repeat this cycle of orientation for each nearby flash. This change in ice crystal orientation from primarily horizontal to vertical during the development of strong vertical electric fields prior to a lightning flash forms the physical basis for anticipating lightning initiation and, potentially, cessation. Research has shown that radar reflectivity (Z) and other co-polar back-scattering radar measurements like differential reflectivity (Z(sub dr)) typically measured by operational dual-polarimetric radars are not sensitive to these changes in ice crystal orientation. However, prior research has demonstrated that oriented ice crystals cause significant propagation effects that can be routinely measured by most dual-polarimetric radars from X-band (3 cm) to S-band (10 cm) wavelengths using the differential propagation phase shift (often just called differential phase, phi(sub dp)) or its range derivative, the specific differential phase (K(sub dp)). Advantages of the differential phase include independence from absolute or relative power calibration, attenuation, differential attenuation and relative insensitivity to ground clutter and partial beam occultation effects (as long as the signal remains above noise). In research mode, these sorts of techniques have been used to anticipate initial cloud electrification, lightning initiation, and cessation. In this study, we develop a simplified model of ice crystal size, shape, orientation, dielectric, and associated radar scattering and propagation effects in order to simulate various idealized scenarios of ice crystals responding to a hypothetical electric field and their dual-polarimetric radar signatures leading up to lightning initiation and particularly cessation. The sensitivity of the K(sub dp) ice orientation signature to various ice properties and radar wavelength will be explored. Since K(sub dp) is proportional to frequency in the Rayleigh- Gans scattering regime, the ice orientation signatures should be more obvious at higher (lower) frequencies (wavelengths). As a result, simulations at radar wavelengths from 10 cm down to 1 cm (Ka-band) will be conducted. Resonance effects will be considered using the T-matrix method. Since most K(sub dp) Vbased observations have been shown at S-band, we will present ice orientation signatures from C-band (UAH/NASA ARMOR) and X-bd (UAH MAX) dual-polarimetric radars located in Northern Alabama. Issues related to optimal radar scanning for the detection of oriented ice will be discussed. Preliminary suggestions on how these differential phase signatures of oriented ice could contribute to lightning initiation and cessation algorithms will be presented.

Carey, L.D.↗