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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Predictive Maturity of Multi-Scale Simulation Models for Fuel Performance

The project proposed to provide a Predictive Maturity Framework with its companion metrics that (1) introduce a formalized, quantitative means to communicate information between interested parties, (2) provide scientifically dependable means to claim completion of Validation and Uncertainty Quantification (VU) activities, and (3) guide the decision makers in the allocation of Nuclear Energy’s resources for code development and physical experiments. The project team proposed to develop this framework based on two complimentary criteria: (1) the extent of experimental evidence available for the calibration of simulation models and (2) the sophistication of the physics incorporated in simulation models. The proposed framework is capable of quantifying the interaction between the required number of physical experiments and degree of physics sophistication. The project team has developed this framework and implemented it with a multi-scale model for simulating creep of a core reactor cladding. The multi-scale model is composed of the viscoplastic self-consistent (VPSC) code at the meso-scale, which represents the visco-plastic behavior and changing properties of a highly anisotropic material and a Finite Element (FE) code at the macro-scale to represent the elastic behavior and apply the loading. The framework developed takes advantage of the transparency provided by partitioned analysis, where independent constituent codes are coupled in an iterative manner. This transparency allows model developers to better understand and remedy the source of biases and uncertainties, whether they stem from the constituents or the coupling interface by exploiting separate-effect experiments conducted within the constituent domain and integral-effect experiments conducted within the full-system domain. The project team has implemented this procedure with the multi- scale VPSC-FE model and demonstrated its ability to improve the predictive capability of the model. Within this framework, the project team has focused on optimizing resource allocation for improving numerical models through further code development and experimentation. Related to further code development, we have developed a code prioritization index (CPI) for coupled numerical models. CPI is implemented to effectively improve the predictive capability of the coupled model by increasing the sophistication of constituent codes. In relation to designing new experiments, we investigated the information gained by the addition of each new experiment used for calibration and bias correction of a simulation model. Additionally, the variability of ‘information gain’ through the design domain has been investigated in order to identify the experiment settings where maximum information gain occurs and thus guide the experimenters in the selection of the experiment settings. This idea was extended to evaluate the information gain from each experiment can be improved by intelligently selecting the experiments, leading to the development of the Batch Sequential Design (BSD) technique. Additionally, we evaluated the importance of sufficiently exploring the domain of applicability in experiment-based validation of high-consequence modeling and simulation by developing a new metric to quantify coverage. This metric has also been incorporated into the design of new experiments. Finally, we have proposed a data-aware calibration approach for the calibration of numerical models. This new method considers the complexity of a numerical model (the number of parameters to be calibrated, parameter uncertainty, and form of the model) and seeks to identify the number of experiments necessary to calibrate the model based on the level of sophistication of the physics. The final component in the project team’s work to improve model calibration and validation methods is the incorporation of robustness to non-probabilistic uncertainty in the input parameters. This is an improvement to model validation and uncertainty quantification stemming beyond the originally proposed scope of the project. We have introduced a new metric for incorporating the concept of robustness into experiment-based validation of numerical models. This project has accounted for the graduation of two Ph.D. students (Kendra Van Buren and Josh Hegenderfer) and two M.S. students (Matthew Egeberg and Parker Shields). One of the doctoral students is now working in the nuclear engineering field and the other one is a post-doctoral fellow at the Los Alamos National Laboratory. Additionally, two more Ph.D. students (Garrison Stevens and Tunc Kulaksiz) who are working towards graduation have been supported by this project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Ab Initio Study of Covalency in the Ground versus Core-Excited States and X-ray Absorption Spectra of Actinide Complexes

Relativistic multireference ab initio wave function calculations within the restricted active space (RAS) framework were performed to calculate metal and ligand X-ray absorption (XAS) near-edge spectroscopy (XANES) intensities for the metal M 4,5 edges of [PuO 2 (H 2 O) 5 ] 2+ , [An VI O 2 ] 2+ (An = U, Np, Pu), and [AmCl 6 ] 3– and the Cl K edge of the Am complex. The extent of An(5f)–ligand bonding was determined via natural localized molecular orbital analyses of the relevant spin–orbit coupled multireference states. The calculated spectra are in good agreement with experiments and allow a detailed assignment of the observed spectral features. The XANES M 4,5 -edge spectra are representative of the actinide orbital covalency in the probed core-excited states, which may be different from the ground-state covalency. Furthermore, an assignment of ground-state An orbital covalency based on XAS spectra should therefore be made with caution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Data-driven design of molecular nanomagnets

Three decades of research in molecular nanomagnets have raised their magnetic memories from liquid helium to liquid nitrogen temperature thanks to a wise choice of the magnetic ion and coordination environment. Still, serendipity and chemical intuition played a main role. In order to establish a powerful framework for statistically driven chemical design, here we collected chemical and physical data for lanthanide-based nanomagnets, catalogued over 1400 published experiments, developed an interactive dashboard (SIMDAVIS) to visualise the dataset, and applied inferential statistical analysis. Our analysis shows that the Arrhenius energy barrier correlates unexpectedly well with the magnetic memory. Furthermore, as both Orbach and Raman processes can be affected by vibronic coupling, chemical design of the coordination scheme may be used to reduce the relaxation rates. Indeed, only bis-phthalocyaninato sandwiches and metallocenes, with rigid ligands, consistently present magnetic memory up to high temperature. Analysing magnetostructural correlations, we offer promising strategies for improvement, in particular for the preparation of pentagonal bipyramids, where even softer complexes are protected against molecular vibrations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Semiclassical dynamics of spin density waves

Here, we present a theoretical framework for equilibrium and nonequilibrium dynamical simulation of quantum states with spin-density-wave (SDW) order. Within a semiclassical adiabatic approximation that retains electron degrees of freedom, we demonstrate that the SDW order parameter obeys a generalized Landau-Lifshitz equation. With the aid of an enhanced kernel polynomial method, our linear-scaling quantum Landau-Lifshitz dynamics (QLLD) method enables dynamical SDW simulations with N ≃ 10 5 lattice sites. Our real-space formulation can be used to compute dynamical responses, such as the dynamical structure factor, of complex and even inhomogeneous SDW configurations at zero or finite temperatures. Applying the QLLD to study the relaxation of a noncoplanar topological SDW under the excitation of a short pulse, we further demonstrate the crucial role of spatial correlations and fluctuations in the SDW dynamics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Classifying topology in photonic crystal slabs with radiative environments

Abstract In the recent years, photonic Chern materials have attracted substantial interest as they feature topological edge states that are robust against disorder, promising to realize defect-agnostic integrated photonic crystal slab devices. However, the out-of-plane radiative losses in those photonic Chern slabs has been previously neglected, yielding limited accuracy for predictions of these systems’ topological protection. Here, we develop a general framework for measuring the topological protection in photonic systems, such as in photonic crystal slabs, while accounting for in-plane and out-of-plane radiative losses. Our approach relies on the spectral localizer that combines the position and Hamiltonian matrices of the system to draw a real-picture of the system’s topology. This operator-based approach to topology allows us to use an effective Hamiltonian directly derived from the full-wave Maxwell equations after discretization via finite-elements method (FEM), resulting in the full account of all the system’s physical processes. As the spectral FEM-localizer is constructed solely from FEM discretization of the system’s master equation, the proposed framework is applicable to any physical system and is compatible with commonly used FEM software. Moving forward, we anticipate the generality of the method to aid in the topological classification of a broad range of complex physical systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Dioxin-Linked Covalent Organic Framework-Supported Palladium Complex for Rapid Room-Temperature Suzuki–Miyaura Coupling Reaction

Covalent organic framework (COF)-supported palladium catalysts have garnered enormous attention for cross-coupling reactions. However, the limited linkage types in COF hosts and their suboptimal catalytic performance have hindered their widespread implementation. Herein, we present the first study immobilizing palladium acetate onto a dioxin-linked COF (Pd/COF-318) through a facile solution impregnation approach. By virtue of its permanent porosity, accessible Pd sites arranged in periodic skeletons, and framework robustness, the resultant Pd/COF-318 exhibits exceptionally high activity and broad substrate scope for the Suzuki–Miyaura coupling reaction between aryl bromides and arylboronic acids at room temperature within an hour, rendering it among the most effective Pd/COF catalysts for Suzuki–Miyaura coupling reactions to date. Moreover, Pd/COF-318 demonstrates excellent recyclability, retaining high activity over five cycles without significant deactivation. The leaching test confirms the heterogeneity of the catalyst. This work uncovers the vast potential of dioxin-linked COFs as catalyst supports for highly active, selective, and durable organometallic catalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Exploitation of Pore Structure for Increased CO 2 Selectivity in Type 3 Porous Liquids

CO 2 capture requires materials with high adsorption selectivity and an industrial ease of implementation. To address these needs, a new class of porous materials was recently developed that combines the fluidity of solvents with the porosity of solids. Type 3 porous liquids (PLs) composed of solvents and metal–organic frameworks (MOFs) offer a promising alternative to current liquid carbon capture methods due to the inherent tunability of the nanoporous MOFs. However, the effects of MOF structural features and solvent properties on CO 2 –MOF interactions within PLs are not well understood. Herein experimental and computational data of CO 2 gas adsorption isotherms were used to elucidate both solvent and pore structure influences on ZIF-based PLs. The roles of the pore structure including solvent size exclusion, structural environment, and MOF porosity on PL CO 2 uptake were examined. A comparison of the pore structure and pore aperture was performed using ZIF-8, ZIF-L, and amorphous-ZIF-8. Adsorption experiments here have verified our previously proposed solvent size design principle for ZIF-based PLs (1.8× ZIF pore aperture). Furthermore, the CO 2 adsorption isotherms of the ZIF-based PLs indicated that judicious selection of the pore environment allows for an increase in CO 2 selectivity greater than expected from the individual PL components or their combination. This nonlinear increase in the CO 2 selectivity is an emergent behavior resulting from the complex mixture of components specific to the ZIF-L + 2'-hydroxyacetophenone-based PL.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

2016 Nuclear Energy Voucher Pilot Program Final Summary

In March 2016, the Department of Energy Office of Nuclear Energy (DOE-NE) Gateway for Accelerated Innovation in Nuclear (GAIN) initiative launched the NE Voucher pilot program for small businesses that develop advanced nuclear technologies. The intent of this program is to provide access to unique physical and intellectual capital that exists within the DOE National Laboratory complex for private-sector developers of innovative nuclear energy technologies. Vouchers allow recipients to have work performed on their behalf at select DOE laboratory facilities. The work is funded by DOE-NE and must be completed within approximately 12 months of the award date. Awards for the pilot had values of $50,000–300,000 each, depending on the complexity of the task requested. The program requires a 20% cost share by voucher recipients. In addition to providing the technical assistance sought by the awardees, the 2016 pilot award cycle showed that the program fosters relationships between these businesses and DOE laboratory staff, serving the GAIN mission to develop a private-public partnership framework that will enable accelerated commercialization of innovative concepts. For the inaugural voucher program, DOE-NE made a total of $2M available. In total, twenty-nine proposals were received and eight (Table 1) were chosen for award based on several criteria, including technical quality, level of innovation, commercialization potential, and relevance to the DOE-NE mission. After the review process, cooperative agreements were finalized, and work on all eight vouchers started in September 2016 and all but one were completed by the end of September, 2017. The single exception was completed in December, 2017.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRSDate not supplied

Recent Advances in Discrete Crack Modeling Applied to Laminated Composites with Emphasis on: Floating Node Method, VCCT and Cohesive Zone Modeling

The present talk will provide an overview of the work performed during the Advanced Composites Project (ACP) on the development, and verification and validation of the Floating Node Method (FNM) as well as the Virtual Crack Closure Technique (VCCT) and cohesive zone modeling (CZM). The FNM is a finite element-based technique to represent crack networks. The complex nature of matrix crack-delamination interactions observed in unidirectional (UD) tape laminates suggests that a methodology such as the FNM method may be required to be able to accurately simulate damage progression in these laminates. Simulating crack onset and growth within the context of the FNM relies on techniques such as VCCT and CZM. The talk is organized to provide, via select examples, an overview of the breadth of the Verification & Validation (V&V) exercises performed during the ACP, and how these challenged the state-of-the art and guided further developments in discrete crack modeling, while helping to establish confidence in the progress made and map the challenges ahead. The performance of the VCCT and CZM individually, and in combination with the FNM can be assessed through verification exercises. These exercises typically consist of a comparison of simulation results to known numerical or analytical solutions. Verification is key to identify implementation issues and limitations that, otherwise, may remain undetected and cloud any subsequent validation efforts. Indeed, a subset of these numerical exercises led to further developments of the VCCT and the FNM method as will be illustrated. Before embarking on the subsequent validation of the framework, it is critical to have adequate characterization data. However, the testing campaign conducted revealed material responses that challenged the state-of-the-art and required further developments. The developments in CZM technology associated with the modeling of the responses of hybrid interfaces (fabric/UD) will be given as an example. Finally, the talk will conclude with a summary of the validation exercises performed under quasi-static and fatigue loadings, highlighting some of the key achievements, outstanding challenges and lessons learned.

finite elements↗
DOE OSTI2019

Spin-State Ordering in Metal-Based Compounds Using the Localized Active Space Self-Consistent Field Method

Quantitatively accurate calculations for spin-state ordering in transition-metal complexes typically demand a robust multiconfigurational treatment. The poor scaling of such methods with increasing size makes them impractical for large, strongly correlated systems. Density matrix embedding theory (DMET) is a fragmentation approach that can be used to specifically address this challenge. The single-determinantal bath framework of DMET is applicable in many situations, but it has been shown to perform poorly for molecules characterized by strong correlation when a multiconfigurational self-consistent field solver is used. To ameliorate this problem, the localized active space self-consistent field (LASSCF) method was recently described. Here in this work, LASSCF is applied to predict spin-state energetics in mono- and di-iron systems, and we show that the model offers an accuracy equivalent to that of CASSCF but at a substantially lower computational cost. Performance as a function of basis set and active space is also examined.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Volatility and Viscosity Are Correlated in Terpene Secondary Organic Aerosol Formed in a Flow Reactor

Secondary organic aerosol (SOA) is a complex mixture of largely unspeciated compounds. Volatility and viscosity of the bulk organic aerosol influence new particle formation, processing, and lifetime in the atmosphere. Relationships between these properties are well-defined for pure compounds, but currently unavailable for bulk organic aerosol. In this survey study, we characterized SOA formed from a range of biogenic precursors and conditions in an oxidation flow reactor for volatility (thermodenuder), viscosity (dimer coagulation, isolation, and coalescence), and oxidation state (aerosol chemical speciation monitor). We find linear trends in log-linear and log-log plots of single-parameter representations of volatility and viscosity, with higher condensed phase fractions of extremely low and low volatility material associated with increased viscosity (R=0.69). Per this relationship, a 10% increase in the contribution of these fractions (i.e., lower volatility) results in an increase in viscosity of approximately 200%. The viscosity (at 30°C) of SOA fell between $6.2 × 10^5$ to $8.0 × 10^8$ Pa s, and thus in the semi-solid range. SOA oxidation state ranged from -1.0 and 0.1, and was weakly anti-correlated with volatility (but not viscosity). We found larger SOA mass loadings generally associated with increased volatility and decreased viscosity. Overall, the results of this preliminary study are consistent with “molecular corridor”-style frameworks employing molecular mass and volatility to estimate viscosity to bulk real-world SOA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Unveiling mesoscopic structures in distorted lamellar phases through deep learning-based small angle neutron scattering analysis

Hypothesis: The formation of distorted lamellar phases, distinguished by their arrangement of crumpled, stacked layers, is frequently accompanied by the disruption of long-range order, leading to the formation of interconnected network structures commonly observed in the sponge phase. Nevertheless, traditional scattering functions grounded in deterministic modeling fall short of fully representing these intricate structural characteristics. Our hypothesis posits that a deep learning method, in conjunction with the generalized leveled wave approach used for describing structural features of distorted lamellar phases, can quantitatively unveil the inherent spatial correlations within these phases. Experiments and Simulations: This report outlines a novel strategy that integrates convolutional neural networks and variational autoencoders, supported by stochastically generated density fluctuations, into a regression analysis framework for extracting structural features of distorted lamellar phases from small angle neutron scattering data. To evaluate the efficacy of our proposed approach, we conducted computational accuracy assessments and applied it to the analysis of experimentally measured small angle neutron scattering spectra of AOT surfactant solutions, a frequently studied lamellar system. Findings: The findings unambiguously demonstrate that deep learning provides a dependable and quantitative approach for investigating the morphology of wide variations of distorted lamellar phases. It is adaptable for deciphering structures from the lamellar to sponge phase including intermediate structures exhibiting fused topological features. In conclusion, this research highlights the effectiveness of deep learning methods in tackling complex issues in the field of soft matter structural analysis and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Atomic-scale mechanism of carbon nucleation from a deep crustal fluid by replica exchange reactive molecular dynamics simulation

Here we present a mechanistic model of carbon nucleation and growth from a fluid at elevated temperature (T) and pressure conditions, typical of those found in the shallow Earth’s lithosphere. Our model uses a replica exchange reactive molecular dynamics framework in which molecular configurations are swapped between adjacent T replica at regular intervals according to underlying statistical mechanics. This framework allows predicting complex molecular structures and thermodynamics while remaining computationally efficient. Here we simulate the reactivity of an unstable mixture of CO 2 and CH 4 at 1000 K and 1 GPa. We find that the path to thermodynamic equilibrium is initially entropy-driven, producing a diversity of short-lived species, including various alcohols with intermediate carbon oxidation states. Cyclic and polycyclic radicals that are sometimes resonance-stabilized form next and set the stage for carbon nucleation. The carbon exsolution process releases abundant water, is exothermic and starts with the nucleation of a large aggregate of hydrogenated graphene flakes from covalently bonded polycyclic units. The carbon backbone of this nucleus subsequently grows into a hydrogen-depleted fullerene-like structure, before evolving toward a partially bilayered graphene layer. Overall, our results show that the mechanism of graphitic C formation is certainly not bimolecular, and that it may involve a combination of key condensation and radical chain reactions. This will help understand the isotopic, and reactive characteristics of carbon-bearing fluids during their upward transit through the Earth’s mantle and crust. Moreover, the mechanistic insights outlined here present intriguing similarities with the process of soot and interstellar dust formation, which suggests that the widespread distribution of abiotic polyaromatic and graphitic material on Earth and beyond may reflect the prevalence of a fundamental chemical pathway.

58 GEOSCIENCES↗
DOE OSTI2022

Off-Gas Design and Testing from Advanced Chlorination Process

Chlorination of Zr alloy cladding with sulfur-chloride reagents is being considered as a means of separating the main metal from alloying elements, imbedded U, actinides, and fission and activation products to purify the Zr. This would allow the Zr to be disposed of as low-level nuclear waste or possibly be recycled. A multistage process was developed that involves several steps and waste streams. Recycling of sulfur-chloride reagents S 2 Cl 2 and SOCl 2 is planned to minimize the waste stream. The generation of off-gas and entrainment of volatiles is anticipated to be minimized. However, given the complex nature of spent nuclear fuel (SNF), some volatile components will be generated, including the solvents themselves; Cl 2 used for the regeneration of S 2 Cl 2 ; volatile fission product chlorides, such as Sb and 3 H; and chlorinated alloying components, such as Sn, Nb, Fe, and Mo. This report discusses the chemical phenomena that might give rise to volatile species and their planned capture. The volatility of the transition metals will depend on their oxidation state and the compounds that are formed, such as Zr tritide. Loading radionuclides in the process off-gas will depend on the inputs to the process. For instance, processing separated Zr to reduce waste will have a much lower loading of radionuclides than if alternative chlorination were used for decladding SNF. Much of the volatile process streams will be part of the solvent recycling, which may involve online scrubbing. Generally, a caustic scrubber should be included in the off-gas to remove acidic vapors (e.g., Cl 2 , SOCl 2 ). The decontamination procedures for removing these species could involve pretreatment (i.e., heating) options or reduction by contact with H 2 . This report discusses these options along with a framework for testing these alternatives in future experiments. Technologies for off-gas capture will leverage those developed in the Materials Recovery and Waste Forms program.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Constraining the particle-scale diversity of black carbon light absorption using a unified framework

Abstract. Atmospheric black carbon (BC), the strongest absorber of visible solar radiation in the atmosphere, manifests across a wide spectrum of morphologies and compositional heterogeneity. Phenomenologically, the distribution of BC among diverse particles of varied composition gives rise to enhancement of its light absorption capabilities by over twofold in comparison to that of nascent or unmixed homogeneous BC. This situation has challenged the modeling community to consider the full complexity and diversity of BC on a per-particle basis for accurate estimation of its light absorption. The conventionally adopted core–shell approximation, although computationally inexpensive, is inadequate not only in estimating but also capturing absorption trends for ambient BC. Here we develop a unified framework that encompasses the complex diversity in BC morphology and composition using a single metric, the phase shift parameter (ρBC), which quantifies how much phase shift the incoming light waves encounter across a particle compared to that in its absence. We systematically investigate variations in ρBC across the multi-space distribution of BC morphology, mixing state, mass, and composition as reported by field and laboratory observations. We find that ρBC>1 leads to decreased absorption by BC, which explains the weaker absorption enhancements observed in certain regional BC compared to laboratory results of similar mixing state. We formulate universal scaling laws centered on ρBC and provide physics-based insights regarding core–shell approximation overestimating BC light absorption. We conclude by packaging our framework in an open-source Python application to facilitate community-level use in future BC-related research. The package has two main functionalities. The first functionality is for forward problems, wherein experimentally measured BC mixing state and assumed BC morphology are input, and the aerosol absorption properties are output. The second functionality is for inverse problems, wherein experimentally measured BC mixing state and absorption are input, and the morphology of BC is returned. Further, if absorption is measured at multiple wavelengths, the package facilitates the estimation of the imaginary refractive index of coating materials by combining the forward and inverse procedures. Our framework thus provides a computationally inexpensive source for calculation of absorption by BC and can be used to constrain light absorption throughout the atmospheric lifetime of BC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Field theoretic simulations of polymer nanocomposites

Polymer field theory has emerged as a powerful tool for describing the equilibrium phase behavior of complex polymer formulations, particularly when one is interested in the thermodynamics of dense polymer melts and solutions where the polymer chains can be accurately described using Gaussian models. However, there are many systems of interest where polymer field theory cannot be applied in such a straightforward manner, such as polymer nanocomposites. Current approaches for incorporating nanoparticles have been restricted to the mean-field level and often require approximations where it is unclear how to improve their accuracy. In this paper, we present a unified framework that enables the description of polymer nanocomposites using a field theoretic approach. This method enables straightforward simulations of the fully fluctuating field theory for polymer formulations containing spherical or anisotropic nanoparticles. We demonstrate our approach captures the correlations between particle positions, present results for spherical and cylindrical nanoparticles, and we explore the effect of the numerical parameters on the performance of our approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Incorporation of shuttle CCT parameters in computer simulation models

Computer simulations of shuttle missions have become increasingly important during recent years. The complexity of mission planning for satellite launch and repair operations which usually involve EVA has led to the need for accurate visibility and access studies. The PLAID modeling package used in the Man-Systems Division at Johnson currently has the necessary capabilities for such studies. In addition, the modeling package is used for spatial location and orientation of shuttle components for film overlay studies such as the current investigation of the hydrogen leaks found in the shuttle flight. However, there are a number of differences between the simulation studies and actual mission viewing. These include image blur caused by the finite resolution of the CCT monitors in the shuttle and signal noise from the video tubes of the cameras. During the course of this investigation the shuttle CCT camera and monitor parameters are incorporated into the existing PLAID framework. These parameters are specific for certain camera/lens combinations and the SNR characteristics of these combinations are included in the noise models. The monitor resolution is incorporated using a Gaussian spread function such as that found in the screen phosphors in the shuttle monitors. Another difference between the traditional PLAID generated images and actual mission viewing lies in the lack of shadows and reflections of light from surfaces. Ray tracing of the scene explicitly includes the lighting and material characteristics of surfaces. The results of some preliminary studies using ray tracing techniques for the image generation process combined with the camera and monitor effects are also reported.

Huntsberger, Terry↗