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At least 1,261 records · Page 70

Statistical Generation of Ocean Forcing With Spatiotemporal Variability for Ice Sheet Models

Melting of ice at the base of floating ice shelves that fringe the Antarctic ice sheet has been identified as a significant source of uncertainty in sea level rise projections. Part of this uncertainty derives from chaotic internal variability of the coupled ocean-atmosphere system. For numerical ice sheet model projections, this uncertainty has not previously been quantified because of the prohibitive computational expense of running large climate model ensembles. Here, we develop and demonstrate a technique that generates independent realizations of internal climate variability from a single climate model simulation. Building on previous developments in model emulation, this technique uses empirical orthogonal function decomposition and Fourier-phase randomization to generate statistically consistent realizations of spatiotemporal variability fields for the target climate variable. The method facilitates efficient sampling of a wide range of climate trajectories, which can also be incorporated within ice sheet or other physical models to represent feedback processes.

54 ENVIRONMENTAL SCIENCES↗

Solid-phase heteroepitaxy of oriented Sb 2 Se 3 on GaAs for birefringent thin films

Here, we investigate the amorphous-to-crystalline transformation of antimony selenide (Sb 2 Se 3 ) on UHV-prepared GaAs (001) substrates. In the bulk orthorhombic form, Sb 2 Se 3 is a layered quasi-1D semiconductor with highly anisotropic properties of interest for optical and electronic devices. We find that an amorphous layer deposited by molecular beam epitaxy annealed at or above 230 °C yields a textured-epitaxial structure among some randomly oriented domains. The textured-epitaxial Sb 2 Se 3 grains are oriented with the covalently bonded “1D axis” constrained in-plane to GaAs [110] and with multiple van der Waals (hk0) orientations out-of-plane. The same texture was achieved exclusively without randomly oriented grains using continuous-wave laser radiation, highlighting the use of thermal and optical methods to yield anisotropic crystalline Sb 2 Se 3 films directly from the amorphous phase. Polarized reflectance and polarized microscopy confirm the unique state of in-plane birefringence in the crystallized thin film. Overall, we show that solid-phase heteroepitaxy provides additional pathways to the integration of low-symmetry chalcogenide semiconductors for demanding applications where the inherent anisotropy needs to be preserved.

Xiao, Kelly [Stanford Univ., CA (United States)] (↗

Sub-pilot-scale Production of High-Value Products from U.S. Coals

Investigators from the University of Utah, University of Wyoming and Marshall University pursued a program to study the conversion of raw coal to high-value products of carbon fiber and silicon carbide. Team members also developed an initial framework for a data portal that can incorporate laboratory data on coal processing and product quality, and also work with tools for machine learning for data analysis, data visualization and economic assessment. Experimental R&D efforts focused on the conversion of raw coal to coal tar and other byproducts, and the resulting tar intermediates were upgraded to form anisotropic and isotropic pitch materials. These pitch materials were produced from coal using both thermal (pyrolysis) and chemical (mild solvolysis liquefaction) decomposition of raw coal. Four different coals were studied: Utah bituminous coal (Sufco), Wyoming PRB coal (Black Thunder), Illinois bituminous coal (Illinois #6), and West Virginia bituminous coal (Flying Eagle). Both metallurgical-grade coking coals and lower-grade steam coals were investigated, and controlled secondary gas-phase reactions were used during a two-stage pyrolysis process to induce cracking and condensation reactions among the pyrolytic tar species. This approach successfully improved the performance of the lower grade coals for yielding pitch materials, with properties more consistent with a commercial-grade pitch that had previously demonstrated success for quality carbon fiber production. The use of waste plastic materials was also studied, to help improve physical and chemical characteristics of the intermediate tars and final pitch product; in particular, for lowering the pitch softening point to an acceptable level for melt spinning carbon fiber. Mild solvolysis liquefaction was also used as a method for producing pitch for carbon fiber production. As expected, significantly higher pitch yields were obtained using this approach, and waste plastic materials were also successfully used to reduce pitch softening point to an acceptable level. The plastic materials were also utilized to create a solvent for the mild solvolysis process, and this plastic-derived solvent was shown to provide results consistent with more expensive commercial chemical solvents, and could thus avoid the need for costly recovery and recycle of a liquefaction solvent. Additional experimental R&D focused on the production of silicon carbide (β-SiC) from the residual char byproduct from pitch production, and also on the production of carbon fiber from the anisotropic pitch. SiC was successfully synthesized using a mixture of residual char and sandstone at a ratio of 1:1. Reaction temperature and residence time were optimized and yielded a product purity of 81%. For carbon fiber production, the most successful pitch samples were obtained from the mild solvolysis liquefaction approach, combined with the use of a plastic (HDPE)-derived solvent. Fiber properties improved over time as laboratory fiber production methodologies improved, and final yields of carbon fiber were obtained with a diameter of 12.14 ± 1.10 um, Modulus of 173.73 ± 15.25 GPa, and Tensile Strength of 1.04 ± 0.10 GPa. A proof-of-concept Modern Community Research Data Portal (MCRDP) was developed and deployed for coal and coal-derived pitch characterization, with the full support of (i) remote web-based access, (ii) distributed analysis, (iii) interactive visualization and exploration, (iv) shared and long-term data access, (v) advanced query capabilities and (vi) real-time collaboration. The Coal to Products Data Portal “coaltoproducts.org” provides researchers with space to store and share data within a project, tools for analyzing and understanding data for scientific investigation, and the ability to publish data to the broader community for reproducibility. The portal leverages the Material Commons 2.0 (MC) platform developed by the Center for PRedictive Integrated Structural Materials Science (PRISMS) of the University of Michigan, to achieve long-term longevity of data collections and, more importantly, collaborative science. A number of data visualization tools were also assessed and implemented for interrogating the experimental and modeling data. The machine learning portion of this project analyzed datasets from two different coal conversion processes performed on a diverse set of coal samples from both the coal pyrolysis experiments and the solvent liquefaction experiments. The work was initiated by exploring standard regression models on the pyrolysis data, aiming to understand the impact of sample characteristics and processing conditions on key product metrics. Over the course of the project, the focus expanded to include a variety of machine learning tools, delving into both supervised and unsupervised learning methods. Models tested on the pyrolysis data included linear, ridge, lasso, elastic-net, Gaussian process, random forest regression, and AutoSklearn, and the approach was continually refined to enhance predictive accuracy and model interpretability. Similar techniques were applied to the liquefaction data with an additional focus on feature engineering. Along with mesophase content, additional outputs of interest were the pitch yield, softening point, and QI content. Insights derived from these analyses are crucial in determining the factors influencing the quality and yield of coal-derived products. As the work progressed, the research evolved from foundational model comparisons to analyses of random forests, decision paths, and feature importance scores. A thorough market analysis was performed to examine the prospects of coal-based carbon fibers. The best opportunities for coal come from its lower and more stable price relative to petroleum, particularly for subbituminous coals, which is the primary advantage that a coal refinery may have over a petroleum refinery. Before a commercial CTP production facility can be modeled, however, several things need to be understood regarding the nature of the would-be coal refinery. These include the technology to be deployed, the size of facility, the volume(s) of co-product(s), and the waste and emissions profile of the plant. The volume of co-products and waste may be substantial and will require separate market analysis to ensure viability. In the near-term, the importance of coal tar pitch, in the form of carbon pitch, to the aluminum and steel industries is likely to overshadow the alternative use of this material as an input for carbon fiber. The importance of steel and aluminum in building materials, and the need for carbon materials in their manufacturing, will ensure that demand for these products remains for the long run. In addition, carbon fiber may also be the best substitute for steel and aluminum well into the future. While society will eventually be able to shift production of much of its electricity needs to renewables, it will not be able to shift away from fossil fuels for production of high-strength construction and vehicular materials. Demand for carbon fiber is expected to increase quickly, but the volume of carbon fiber and the amount of coal that would be needed to produce even a sizeable share of this market may still be relatively small compared to current coal production. Thus, other coal-based products like graphene, graphite, carbon foams, resins, and carbon-based building products will play important roles in sustaining coal production as coal-fired power generation continues to decline.

01 COAL, LIGNITE, AND PEAT↗

Coupled atmosphere/canopy model for remote sensing of plant reflectance features

Solar radiative transfer through a coupled system of atmosphere and plant canopy is modeled as a multiple-scattering problem through a layered medium of random scatterers. The radiative transfer equation is solved by the discrete-ordinates finite-element method. Analytic expressions are derived that allow the calculation of scattering and absorption cross sections for any plant canopy layer form measurable biophysical parameters such as the leaf area index, leaf angle distribution, and individual leaf reflectance and transmittance data. An expression for a canopy scattering phase function is also given. Computational results are in good agreement with spectral reflectance measurements directly above a soybean canopy, and the concept of greenness- and brightness-transforms of Landsat MSS data is reconfirmed with the computed results. A sensitivity analysis with the coupled atmosphere/canopy model quantifies how satellite-sensed spectral radiances are affected by increased atmospheric aerosols, by varying leaf area index, by anisotropic leaf scattering, and by non-Lambertian soil boundary conditions. Possible extensions to a 2-D model are also discussed.

Gerstl, S. A.↗

Estimating the signal-to-noise ratio of AVIRIS data

To make the best use of narrowband airborne visible/infrared imaging spectrometer (AVIRIS) data, an investigator needs to know the ratio of signal to random variability or noise (signal-to-noise ratio or SNR). The signal is land cover dependent and varies with both wavelength and atmospheric absorption; random noise comprises sensor noise and intrapixel variability (i.e., variability within a pixel). The three existing methods for estimating the SNR are inadequate, since typical laboratory methods inflate while dark current and image methods deflate the SNR. A new procedure is proposed called the geostatistical method. It is based on the removal of periodic noise by notch filtering in the frequency domain and the isolation of sensor noise and intrapixel variability using the semi-variogram. This procedure was applied easily and successfully to five sets of AVIRIS data from the 1987 flying season and could be applied to remotely sensed data from broadband sensors.

Curran, Paul J.↗

An analytic treatment of gravitational microlensing for sources of finite size at large optical depths

Statistical methods are developed for gravitational lensing in order to obtain analytic expressions for the average surface brightness that include the effects of microlensing by stellar (or other compact) masses within the lensing galaxy. The primary advance here is in utilizing a Markoff technique to obtain expressions that are valid for sources of finite size when the surface density of mass in the lensing galaxy is large. The finite size of the source is probably the key consideration for the occurrence of microlensing by individual stars. For the intensity from a particular location, the parameter which governs the importance of microlensing is determined. Statistical methods are also formulated to assess the time variation of the surface brightness due to the random motion of the masses that cause the microlensing.

Deguchi, Shuji↗

Estimation of signal-to-noise - A new procedure applied to AVIRIS data

To make the best use of narrowband airborne visible/infrared imaging spectrometer (AVIRIS) data, an investigator needs to know the ratio of signal to random variability or noise (signal-to-noise ratio or SNR). The signal is land cover dependent and varies with both wavelength and atmospheric absorption; random noise comprises sensor noise and intrapixel variability (i.e., variability within a pixel). The three existing methods for estimating the SNR are inadequate, since typical laboratory methods inflate while dark current and image methods deflate the SNR. A new procedure is proposed called the geostatistical method. It is based on the removal of periodic noise by notch filtering in the frequency domain and the isolation of sensor noise and intrapixel variability using the semi-variogram. This procedure was applied easily and successfully to five sets of AVIRIS data from the 1987 flying season and could be applied to remotely sensed data from broadband sensors.

Curran, Paul J.↗

Test particle calculations of pick-up ions in the vicinity of Comet Giacobini-Zinner

Ionization of cometary neutral molecules produces ions which are picked-up by the solar wind. The cometary ion pick-up process for Comet Giacobini-Zinner is studied using a test particle method in which trajectories are numerically calculated for several thousand ions whose initial locations were chosen randomly with probability proportional to the neutral density. The cometary ion distribution function was calculated at several locations upstream of the bow shock. Several types of magnetic fluctuations were included. Circularly and linearly polarized monochromatic waves result in less pitch-angle scattering of pick-up ions than turbulent fluctuations which have about the same amplitude. Some anisotropy remains in the distribution function just upstream of the shock, even for the turbulent fluctuations.

Cravens, T. E.↗

Theoretical calculations of ion acceleration in the vicinity of comet Giacobini-Zinner

Ionization of cometary neutral molecules produces ions which are picked up by the solar wind. The cometary ion pickup process for comet Giacobini-Zinner is studied in two ways: (1) with a test particle method in which trajectories are numerically calculated for several thousand ions whose initial locations were chosen randomly with probability proportional to the neutral density and (2) with a quasi-linear diffusion model. The cometary ion distribution function was calculated with the test particle model at several locations upstream of the bow shock and for several types of magnetic fluctuations (or waves). These waves were allowed to propagate in both directions along the magnetic field at the Alfven speed. Both pitch angle scattering and energy diffusion are evident in the derived ion distributions. The monochromatic waves result in less ion acceleration than turbulent fluctuations with about the same amplitude. The calculated ion distribution functions are in reasonable agreement with the distributions measured in the vicinity of comet Giacobini-Zinner in 1985 by particle detectors on the ICE spacecraft when the ratio of power in sunward propagating Alfven waves to the power in antisunward propagating waves is assumed to lie between about 20% and 50%. However, the quasi-linear diffusion model results agree best with the measured distribution functions when the power ratio is only about 3 percent.

Mckenzie, M. L.↗

Soil Sampling Techniques For Alabama Grain Fields

Characterizing the spatial variability of nutrients facilitates precision soil sampling. Questions exist regarding the best technique for directed soil sampling based on a priori knowledge of soil and crop patterns. The objective of this study was to evaluate zone delineation techniques for Alabama grain fields to determine which method best minimized the soil test variability. Site one (25.8 ha) and site three (20.0 ha) were located in the Tennessee Valley region, and site two (24.2 ha) was located in the Coastal Plain region of Alabama. Tennessee Valley soils ranged from well drained Rhodic and Typic Paleudults to somewhat poorly drained Aquic Paleudults and Fluventic Dystrudepts. Coastal Plain s o i l s ranged from coarse-loamy Rhodic Kandiudults to loamy Arenic Kandiudults. Soils were sampled by grid soil sampling methods (grid sizes of 0.40 ha and 1 ha) consisting of: 1) twenty composited cores collected randomly throughout each grid (grid-cell sampling) and, 2) six composited cores collected randomly from a -3x3 m area at the center of each grid (grid-point sampling). Zones were established from 1) an Order 1 Soil Survey, 2) corn (Zea mays L.) yield maps, and 3) airborne remote sensing images. All soil properties were moderately to strongly spatially dependent as per semivariogram analyses. Differences in grid-point and grid-cell soil test values suggested grid-point sampling does not accurately represent grid values. Zones created by soil survey, yield data, and remote sensing images displayed lower coefficient of variations (8CV) for soil test values than overall field values, suggesting these techniques group soil test variability. However, few differences were observed between the three zone delineation techniques. Results suggest directed sampling using zone delineation techniques outlined in this paper would result in more efficient soil sampling for these Alabama grain fields.

Thompson, A. N.↗

Estimation of Sonic Fatigue by Reduced-Order Finite Element Based Analyses

A computationally efficient, reduced-order method is presented for prediction of sonic fatigue of structures exhibiting geometrically nonlinear response. A procedure to determine the nonlinear modal stiffness using commercial finite element codes allows the coupled nonlinear equations of motion in physical degrees of freedom to be transformed to a smaller coupled system of equations in modal coordinates. The nonlinear modal system is first solved using a computationally light equivalent linearization solution to determine if the structure responds to the applied loading in a nonlinear fashion. If so, a higher fidelity numerical simulation in modal coordinates is undertaken to more accurately determine the nonlinear response. Comparisons of displacement and stress response obtained from the reduced-order analyses are made with results obtained from numerical simulation in physical degrees-of-freedom. Fatigue life predictions from nonlinear modal and physical simulations are made using the rainflow cycle counting method in a linear cumulative damage analysis. Results computed for a simple beam structure under a random acoustic loading demonstrate the effectiveness of the approach and compare favorably with results obtained from the solution in physical degrees-of-freedom.

Rizzi, Stephen A.↗

VAPEPS Management Center

A VibroAcoustic Payload Environment Prediction System (VAPEPS) Management Center is established and being maintained at JPL. VAPEPS is a computer program that utilizes statistical energy analysis (SEA) theory and SEA extrapolation methods to predict the vibroacoustic environments of complex systems. The program is commonly utilized to establish random vibration and acoustic test requirements for aerospace components exposed to launch environments. It can also be used in the payload or launch vehicle design process for control or mitigation of the launch or on-orbit vibration and acoustic environments, as well as to calculate acoustically induced stresses in structures such as solar panels and reflectors.

VAPEPS↗

Probabilistic Modeling of a Three-Stage Human Landing System Architecture

Space Policy Directive-1 has led to NASA partnerships with commercial entities on procurement which includes the development of the Human Landing System (HLS) [1]. With the goal of delivering human crew to the lunar surface by 2024, system uncertainties become an important obstacle to the maturation of multiple new, driving technologies and mission concepts of the HLS program. As unmitigated uncertainties have previously led to failed development programs, these risks and their impacts must be understood and handled to ensure program success [2]. Sources of uncertainty include novel engine designs and configurations, increased reliance on cryogenic fluid management(CFM), and refueling technologies—which propagate as high-level performance metrics such as overall propellant mass and engine performance. Also, the occurrence of operational uncertainties—e.g. launch conditions or need to abort during the mission—can cause cascading effects on the rest of the mission that are difficult to definitively quantify, and are outside the scope of control. These concrete examples and other occurrences can be categorized as either epistemic or aleatory uncertainties.Epistemic uncertainty arises due to a lack of knowledge and can be alleviated with design and program maturation. Aleatory uncertainty is due to the inherent randomness of the system and cannot be directly reduced, unlike epistemic uncertainty. Robust design and probabilistic methods can compensate for aleatory effects. A taxonomy of uncertainty is referred to for this work [3]. In this paper, a probabilistic methodology to handle uncertainties has been demonstrated on a three-element HLS concept [1, 4], which allows tracking of current best estimates of the concept and assessment of concept design robustness against uncertainties. A sample case has been completed for this abstract, and an expansion on the methodology will be included in the final paper. This methodology has two key parts: first, the creation of a dynamic architecture model of a three-element HLS concept; and second, its use with surrogate modeling and range estimating techniques to capture and propagate uncertainties. This abstract will cover the basics of the approach used, and further details and justifications will be in the final paper.The mission profile associated with this three-element concept (Fig 1) was modeled as a set of mission events that facilitated mass changes, idles, or spacecraft maneuvers. The mission profile scope starts with each element’s NRHO orbit insertion and aggregation and ends at post-sortie rendezvous with Orion. More detail on the mission profile will be in the final paper. The DYnamic Rocket EQuation Tool (DYREQT), a space systems synthesis and sizing framework used by NASA, was used as the physics framework to model the HLS architecture for applying the probabilistic methodology [5, 6]. Specifically, a parametric representation of the lander, ascent, and transfer elements and the mission profile of each element was established, with vehicle and mission parameters available as inputs to allow for a dynamic model. Each vehicle stage was modeled with high-level performance metrics, using Isp and propellant mass fraction (PMF) to remain parametric. For the probabilistic analysis, uncertainties of interest within the HLS concept were enumerated and represented as parameters within the DYREQT model as inputs for vehicle stages or mission profile events. These parameters were frozen at their nominal values for the purposes of baselining architecture performance and sizing the vehicle appropriately based on reference documentation [1]. Range estimating—a probabilistic method that combines Monte Carlo sampling, focus on critical parameters, and heuristics to assess risk and opportunities—is traditionally used with Mass Equipment Lists (MELs), but has been adapted with operational parameters as well as vehicle parameters in theDYREQT model to capture mission uncertainty alongside vehicle uncertainty [7, 3]. This method was selected due to its application and insight on a system from a bottom-up perspective, independence from historical rules of thumb, and ability to generate sensitivities based on design decisions and uncertainties. As a sample case for the abstract, the boiloff rates of the vehicle elements and the loiter times during the mission (simulating launch time variations and changing window of opportunities) were used with range estimating to provide preliminary results. To perform the range estimation portion of this methodology (depicted in Fig. 3, further details in final paper), the DYREQT model was sampled using a Design of Experiments (DoE) to efficiently explore the architecture design space with respect to the sample set of uncertainty parameters; 5,000 cases via Latin Hypercube Sampling were computed on the DYREQT architecture model. Then, the results were used to create surrogate models, multivariate regressions that can visualize hypercube trends in the design space, of the architecture with respect to the uncertainty parameters. Range estimating was applied to the surrogates instead of the actual models, which saves computational expense due to the bulk of cases needed for the Monte Carlo simulation as part of range estimating. Uncertainty parameters were sampled independently from triangular distributions using the DoE ranges as ‘min’ and ‘max’, and the nominal value as ‘most likely’. Based engineering intuition, some uncertainty parameters are correlated—e.g. if the main propellant has a high boil-off rate, the oxidizer should follow suit as both are related to CFM technology.While a Monte Carlo simulation samples all inputs as independent, the results would show model correlations; thus, it is efficient to sample the inputs as correlated. Using a correlation matrix constructed for the uncertainty parameters, previously independent samples were transformed to perform a Correlated Monte Carlo. A table for the DoE ranges and probability distribution parameters is shown in Table 1, and more details on Correlated Monte Carlo Simulations will be discussed in the final paper. The model’s resulting DoE showed that multivariate polynomial equations fit via least squares method captured its behavior accurately for the sample case. For the Correlated Monte Carlo Simulation, a positive correlation between fuel and oxidizer boiloff rates was used as a demonstration. 10,000 cases were computed with the surrogates and the launched masses for each vehicle element was collated. The results can be displayed in a probability density function (PDF), showing the impact of the uncertainty parameters chosen. Integrating the PDFs will yield a cumulative distribution function (CDF) that shows the cumulative probability of a given value on the x-axis. For the sample case, the elements’ launch mass margin was calculated and represented in as CDFs, as a demonstrated representation of figures of merit for the HLS concept. For the lander and ascent elements, the NRHO mass insertion limit is 16t; the transfer element has a limit of 30t [1]. It can be seen with Figure 2 that this probabilistic methodology can provide insight into mass margin with respect to the uncertainties being modeled. Currently, the results show that the lander (descent) vehicle element has the most restrictive design space; it is the only element to show a 10% probability of negative margin. Further analysis on the Monte Carlo results will show sensitivities for driving constraints and parameters for architecture feasibility, which can lead to establishing potential mission rules.The combination of range estimating with a parametric architecture model for HLS demonstrated the capability of this probabilistic methodology in a sample case. As the HLS development progresses, this methodology has the potential for keeping current best estimates of architecture performance for awarded concepts due to the flexibility in DYREQT’s modeling framework and its parametric nature. Concept maturation and increased epistemic knowledge can be injected into the model probabilistic modeling, and thus continue to track probability of mission success.

Stephanie Y Zhu↗

Carbon Nanotube – Polysiloxane Nanocomposites for Ablative Thermal Protection Systems

Ultra-high temperature resins (UHTR) such as polysiloxane possess excellent characteristics for ablation including low thermal conductivity, lightweight composition, high thermal resistance, and the ability to form a durable char layer. To enhance its mechanical strength, the aerospace industry utilizes fiber reinforcement, such as carbon fiber reinforced polysiloxane (CF-polysiloxane), due to its high strength-to-weight ratio. Carbon nanotubes (CNTs) have advantages over microfibers including higher specific strength, lower density, and customizable thermal conductivity. Their nano-scale dimensions allow for a more homogenous material compared to traditional microfibers. Conventional methods of incorporating CNTs into resins often have structural defects such as voids, CNT agglomerations, and randomly dispersed CNTs, resulting in marginal improvements in properties. A novel approach known as bulk nanocomposite laminating (BNL) has been introduced involving CNT densification, resin polymer infiltration, and pressurized curing to achieve a high packing density exceeding 35% by volume. Characterization and testing to simulate re-entry conditions is performed with a sample of CNT-polysiloxane nanocomposite cured onto a CF-polysiloxane backing. These samples are subjected to ablation by an oxyacetylene flame while collecting temperature data to evaluate thermal protection properties.

Palak B Patel↗

Kinetic Plasma Simulation Capabilities in the MOOSE Framework: Verification of Particle-Particle Collisions

High-fidelity simulations of complex plasma systems allow researchers to gain key insights into and understanding of these systems. To facilitate massively parallel high-fidelity plasma simulations, finite-element-based particle-in-cell capabilities are being developed within the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) based framework called Software for Advanced Large-scale Analysis of MAgnetic confinement for Numerical Design, Engineering & Research (SALAMANDER). While SALAMANDER’s primary objective is modeling edge plasmas and plasma-facing components in fusion devices, the particle-in-cell capabilities being developed are general and will support modeling low-temperature plasmas as well. Previously, collisionless magnetostatic simulation capabilities have been verified with the two-stream and Dorey-Guest-Harris instabilities, and single particle motion. Collisions were implemented using the direct simulation Monte Carlo method, and verification of this capability will be presented here several verification problems: relaxation of a randomly initialized gas to a Maxwellian distribution, Fourier heat flow, and comparison of reaction rates to both analytic calculations and those calculated using a multi-term Boltzmann solver.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Overview of Methods for Deriving the Radiative Transfer Theory from the Maxwell Equations. I: Approach Based on the Far-Field Foldy Equations

In this paper, we revisit, with further enhancements and clarifications, the self-consistent first-principles approach developed previously for deriving the vector radiative transfer theory for a discrete random medium with a sparse concentration of particles. We specifically consider the case of a plane-parallel particulate layer embedded in an otherwise homogeneous unbounded medium. The solution method is based on the far-field Foldy equations, an order-of-scattering expansion for the total field derived under the Twersky approximation, the computation of the coherent field by assuming that the positions of the particles are uncorrelated, and the ladder approximation for the coherency dyadic. The latter yields an integral equation for the diffuse specific coherency dyadic, defined through an angular spectrum repre- sentation for the coherency dyadic, which in turn, gives the vector radiative transfer equation for the diffuse specific intensity column vector. We analyze specifically the computation of the coherent field for inhomogeneous particulate media and multiple species of particles, the continuous extension of the far-field representation to the near field, the Foldy approximation, and the Foldy integral equation for the coherent field. Finally, we discuss the transition from the vector to the scalar radiative transfer equation.

Doicu, Adrian↗

Optical devices and methods employing nanoparticles, microcavities, and semicontinuous metal films

An optical sensing enhancing material (and corresponding method of making) comprising: a medium, the medium comprising a plurality of aggregated nanoparticles comprising fractals; and a microcavity, wherein the medium is located in a vicinity of the microcavity. Also an optical sensor and sensing method comprising: providing a doped medium, the medium comprising a plurality of aggregated nanoparticles comprising fractals, with the material; locating the doped medium in the vicinity of a microcavity; exciting the doped medium with a light source; and detecting light reflected from the doped medium. Also an optical sensing enhancing material comprising a medium, the medium comprising a semicontinuous metal film of randomly distributed metal particles and their clusters at approximately their percolation threshold. The medium preferably additionally comprises a microcavity/microresonator. Also devices and methods employing such material.

Armstrong, Robert L.↗