Evaluation of optical thin-film filters with a digital computer and display
Multilayer, dielectric, thin film optical filter evaluation using cathode ray tube display device
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Multilayer, dielectric, thin film optical filter evaluation using cathode ray tube display device
This paper demonstrates the use of a computer-based optical method for locating the positions of nodes and antinodes in vibrating members. Structured light patterns are projected at an angle onto the vibrating surface using a 35 mm slide projector. The vibrating surface and the projected images are captured in a time averaged photograph which is subsequently digitized. The inherent fringe patterns are filtered to determine amplitudes of vibration, and computer programs are used to compare the time averaged images to images recorded prior to excitation to locate nodes and antinodes. Some of the influences of pattern regularity on digital correlation are demonstrated, and a speckle-based method for determining the mode shapes and the amplitudes of vibration with variable sensitivity is suggested.
Fast computer-controlled sampling of optical knife-edge response (KER) signal increases accuracy of optical system aberration measurement. Submicrosecond-response detectors in optical focal plane convert optical signals to electrical signals converted to digital data, sampled and feed into computer for storage and subsequent analysis. Optical data are virtually free of effects of index-of-refraction gradients.
Purpose: To develop and validate a Monte Carlo (MC) model of a novel multi-layer imager (MLI) for megavolt (MV) energy beams. The MC model will enable performance optimization of the MLI design for clinical applications including patient setup verification, tumor tracking and MVCBCT. Methods: The MLI is composed of four layers of converter, scintillator and light detector, each layer similar to the current clinical AS1200 detector (Varian Medical Systems, Inc). The MLI model was constructed using the Geant4 Application for Tomographic Emission (GATE v7.1) and includes interactions for x-ray photons, charged particles and optical photons. Computational experiments were performed to assess Modulation Transfer Function (MTF), Detective Quantum Efficiency (DQE) and Noise Power Spectrum normalized by photon fluence and average detector signal (qNNPS). Results were compared with experimental measurements. The current work incorporates, in one model, the complete chain of events occurring in the imager; i.e. starting from x-ray interaction to charged particle transport and energy deposition to subsequent generation, interactions and detection of optical photons. Results: There is good agreement between measured and simulated MTF, qNNPS and DQE values. Normalized root mean squared error (NRMSE) between measured and simulated values over all four layers was 2.18%, 2.43% and 6.05% for MTF, qNNPS and DQE respectively. The relative difference between simulated and measured values for qNNPS(0) was 1.68% and 1.57% for DQE(0). Current results were obtained using a 6MV Varian Truebeam™ spectrum. Conclusion: A comprehensive Monte Carlo model of the MLI prototype was developed to allow optimization of detector components. The model was assessed in terms of imaging performance using standard metrics (i.e. MTF, qNNPS, DQE). Good agreement was found between simulated and measured values. The model will be used to assess alternative detector constructions to facilitate advanced clinical imaging applications including MV-CBCT and tumor tracking. The project was supported, partially, by a grant from Varian Medical Systems, Inc., and Award No. R01CA188446-01 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health.
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The Kubo-Greenwood (KG) formula is often used in conjunction with Kohn-Sham (KS) density functional theory (DFT) to compute the optical conductivity, particularly for warm dense matter. For applying the KG formula, all KS eigenstates and eigenvalues up to an energy cutoff are required and thus the approach becomes expensive, especially for high temperatures and large systems, scaling cubically with both system size and temperature. Here, we develop an approach to calculate the KS conductivity within the stochastic DFT framework, which requires knowledge only of the KS Hamiltonian but not its eigenstates and values. We show that the computational effort associated with the method scales linearly with system size and reduces in proportion to the temperature, unlike the cubic increase with traditional deterministic approaches. In addition, we find that the method allows an accurate description of the entire spectrum, including the high-frequency range, unlike the deterministic method which is compelled to introduce a high-frequency cutoff due to memory and computational time constraints. Finally, we apply the method to helium-hydrogen mixtures in the warm dense matter regime at temperatures of ~60 kK and find that the system displays two conductivity phases, where a transition from nonmetal to metal occurs when hydrogen atoms constitute ~0.3 of the total atoms in the system.
This research was initiated as a part of the effort at the NASA Ames Research Center to design a computer vision based system that can enhance the safety of navigation by aiding the pilots in detecting various obstacles on the runway during critical section of the flight such as a landing maneuver. The primary goal is the development of algorithms for detection of moving objects from a sequence of images obtained from an on-board video camera. Image regions corresponding to the independently moving objects are segmented from the background by applying constraint filtering on the optical flow computed from the initial few frames of the sequence. These detected regions are tracked over subsequent frames using a model based tracking algorithm. Position and velocity of the moving objects in the world coordinate is estimated using an extended Kalman filter. The algorithms are tested using the NASA line image sequence with six static trucks and a simulated moving truck and experimental results are described. Various limitations of the currently implemented version of the above algorithm are identified and possible solutions to build a practical working system are investigated.
Here, we have applied the nonlinear map method to comprehensively characterize the chromatic optics in particle accelerators. Our approach is built on the foundation of symplectic transfer maps of magnetic elements. The chromatic lattice parameters can be transported from one element to another by the maps. We also introduce a Jacobian operator that provides an intrinsic linkage between the maps and the matrix with parameter dependence. The link allows us to directly apply the formulation of the linear optics to compute the chromatic lattice parameters. As an illustration, we analyze an alternating-gradient cell with nonlinear sextupoles, octupoles, and decapoles and derive analytically their settings for the local chromatic compensation. Finally, the cell becomes nearly perfect up to the third-order of the momentum deviation.
Zernike polynomials serve as an orthogonal basis on the unit disc, and have proven to be effective in optics simulations, astrophysics, and more recently in plasma simulations. Unlike Bessel functions, Zernike polynomials are inherently finite and smooth at the disc center (r=0), ensuring continuous differentiability along the axis. This property makes them particularly suitable for simulations, requiring no additional handling at the origin. We developed ZERNIPAX, an open-source Python package capable of utilizing CPU/GPUs, leveraging Google's JAX package and available on GitHub as well as the Python software repository PyPI. Furthermore, our implementation of the recursion relation between Jacobi polynomials significantly improves computation time compared to alternative methods by use of parallel computing while still performing more accurately for high-mode numbers.
A theory is described for computing the reflected or scattered field from a smooth body with inflection points. These inflections occur in certain directions at each surface point for which the total (Gaussian) curvature is zero or negative. For surface illumination in one of these critical directions, the usual reflection formulas obtained by the high-frequency approximation are inapplicable, and a shadow zone exists in the reflected field. Scattering into the shadow zone is treated, as well as specular reflection. This theory should have a variety of applications such as for certain optics problems, computer graphics modeling of three-dimensional shapes, and the design and analysis of specialized microwave reflector antennas.
The Biophysics and Advanced Materials Branch of the Microgravity Science and Applications Division at Marshall Space Flight Center has been investigating polymers with the potential for nonlinear optical (NLO) applications for a number of years. Some of the potential applications for NLO materials include optical communications, computing, and switching. To this point the branch's research has involved polydiacetylenes, phthalocyanins, and other synthetic polymers which have inherent NLO properties. The aim of the present research is to investigate the possibility of using naturally occurring polymers such as polysaccharides or proteins to trap and align small organic molecules with useful NLO properties. Ordering molecules with NLO properties enhances 3rd order nonlinear effects and is required for 2nd order nonlinear effects. Potential advantages of such a system are the flexibility to use different small molecules with varying chemical and optical properties, the stability and cost of the polymers, and the ability to form thin, optically transparent films. Since the quality of any polymer films depends on optimizing ordering and minimizing defects, this work is particularly well suited for microgravity experiments. Polysaccharide and protein polymers form microscopic crystallites which must align to form ordered arrays. The ordered association of crystallites is disrupted by gravity effects and NASA research on protein crystal growth has demonstrated that low gravity conditions can improve crystal quality.
In this paper, we study the problem of Cross-View Person Identification (CVPI), which aims at identifying the same person from temporally synchronized videos taken by different wearable cameras. Our basic idea is to utilize the human motion consistency for CVPI, where human motion can be computed by optical flow. However, optical flow is view-variant - the same person's optical flow in different videos can be very different due to view angle change. In this paper, we attempt to utilize 3D human-skeleton sequences to learn a model that can extract view-invariant motion features from optical flows in different views. For this purpose, we use 3D Mocap database to build a synthetic optical flow dataset and train a Triplet Network (TN) consisting of three sub-networks: two for optical flow sequences from different views and one for the underlying 3D Mocap skeleton sequence. Finally, sub-networks for optical flows are used to extract view-invariant features for CVPI. Experimental results show that, using only the motion information, the proposed method can achieve comparable performance with the state-of-the-art methods. Further combination of the proposed method with an appearance-based method achieves new state-of-the-art performance.
A computational method was devised to explore the relationship between charge separation, geometry, molecular dipole moment, polarizability, and hyperpolarizabilities in comjugated organic molecules. It is shown that bond length alternation (the average difference in length between single and double bonds in the molecule) is a key structurally observable parameter that can be correlated with hyperpolarizabilities and is thus relevant to the optimizaton of molecules and materials.
The effect of thin cirrus clouds in retrieving the dust optical depth from MODIS observations is investigated by using a simplified aerosol retrieval algorithm based on the principles of the Deep Blue aerosol property retrieval method. Specifically, the errors of the retrieved dust optical depth due to thin cirrus contamination are quantified through the comparison of two retrievals by assuming dust-only atmospheres and the counterparts with overlapping mineral dust and thin cirrus clouds. To account for the effect of the polarization state of radiation field on radiance simulation, a vector radiative transfer model is used to generate the lookup tables. In the forward radiative transfer simulations involved in generating the lookup tables, the Rayleigh scattering by atmospheric gaseous molecules and the reflection of the surface assumed to be Lambertian are fully taken into account. Additionally, the spheroid model is utilized to account for the nonsphericity of dust particles In computing their optical properties. For simplicity, the single-scattering albedo, scattering phase matrix, and optical depth are specified a priori for thin cirrus clouds assumed to consist of droxtal ice crystals. The present results indicate that the errors in the retrieved dust optical depths due to the contamination of thin cirrus clouds depend on the scattering angle, underlying surface reflectance, and dust optical depth. Under heavy dusty conditions, the absolute errors are comparable to the predescribed optical depths of thin cirrus clouds.
This Laboratory Directed Research and Development project developed and applied closely coupled experimental and computational tools to investigate powder compaction across multiple length scales. The primary motivation for this work is to provide connections between powder feedstock characteristics, processing conditions, and powder pellet properties in the context of powder-based energetic components manufacturing. We have focused our efforts on multicrystalline cellulose, a molecular crystalline surrogate material that is mechanically similar to several energetic materials of interest, but provides several advantages for fundamental investigations. We report extensive experimental characterization ranging in length scale from nanometers to macroscopic, bulk behavior. Experiments included nanoindentation of well-controlled, micron-scale pillar geometries milled into the surface of individual particles, single-particle crushing experiments, in-situ optical and computed tomography imaging of the compaction of multiple particles in different geometries, and bulk powder compaction. In order to capture the large plastic deformation and fracture of particles in computational models, we have advanced two distinct meshfree Lagrangian simulation techniques: 1.) bonded particle methods, which extend existing discrete element method capabilities in the Sandia-developed , open-source LAMMPS code to capture particle deformation and fracture and 2.) extensions of peridynamics for application to mesoscale powder compaction, including a novel material model that includes plasticity and creep. We have demonstrated both methods for simulations of single-particle crushing as well as mesoscale multi-particle compaction, with favorable comparisons to experimental data. We have used small-scale, mechanical characterization data to inform material models, and in-situ imaging of mesoscale particle structures to provide initial conditions for simulations. Both mesostructure porosity characteristics and overall stress-strain behavior were found to be in good agreement between simulations and experiments. We have thus demonstrated a novel multi-scale, closely coupled experimental and computational approach to the study of powder compaction. This enables a wide range of possible investigations into feedstock-process-structure relationships in powder-based materials, with immediate applications in energetic component manufacturing, as well as other particle-based components and processes.
In this paper, we report that terahertz (THz) irradiation of mouse mesenchymal stem cells (mMSCs) with a single-frequency (SF) 2.52 THz laser or pulsed broadband (centered at 10 THz) source results in irradiation specific heterogenic changes in gene expression. The THz effect depends on irradiation parameters such as the duration and type of THz source, and on the degree of stem cell differentiation. Our microarray survey and RT-PCR experiments demonstrate that prolonged broadband THz irradiation drives mMSCs toward differentiation, while 2-hour irradiation (regardless of THz sources) affects genes transcriptionally active in pluripotent stem cells. The strictly controlled experimental environment indicates minimal temperature changes and the absence of any discernable response to heat shock and cellular stress genes imply a non-thermal response. Computer simulations of the core promoters of two pluripotency markers reveal association between gene upregulation and propensity for DNA breathing. Finally, we propose that THz radiation has potential for non-contact control of cellular gene expression.
Introduction The Lockheed Martin Orion spacecraft conducted the Artemis I flight around the Moon from November 16 through December 11, 2022. After the flight, an engineer from the NASA Johnson Space Center (JSC) Hypervelocity Impact Technology (HVIT) Group performed a Micrometeoroid and Orbital Debris MMOD analysis using the Bumper 3 risk assessment tool to predict the number of small impacts that would likely have occurred during the mission. Separately, a team from the same group inspected the Orion capsule for hypervelocity impact damage features. The results of the inspection were compared to those of the analysis to aid in improving the analysis, including the environment models. Scope of Work The spacecraft geometry model was created by Lockheed Martin during construction of the Artemis I Orion vehicle based on Computer Aided Design (CAD) models of the vehicle. New hypervelocity impact testing was performed to verify Ballistic Limit Equations (BLEs) used in the analysis to link impactor size and damage to the Thermal Protection System (TPS). The exact trajectory flown was recorded during the flight, including vehicle attitude. This data was used in conjunction with the ORDEM 3.2 and MEM 3 environment modeling tools to create models of particle flux impacting the spacecraft throughout the mission. Meteoroid shower forecast information was also included to account for additional particle flux associated with meteoroid showers. Inspection of the Orion capsule included the Backshell thermal tiles and the tape covering it, windows, fabric thermal materials, and small areas of other materials. Potential MMOD damage found was characterized using various techniques, including optical microscopy, computed tomography scanning, and X-ray spectroscopy. Findings The number of craters found in the Backshell tile, and their size distribution, matches well with the Bumper analysis prediction. Tape, window, and other material impacts recorded similarly align to Bumper analysis predictions. Conclusions and Recommendations This comparison of analysis with inspection of the hardware provides valuable insight into the MMOD environment and how accurately analysis tools assess the impact risk to spacecraft. As this was the first large, non-ablative returned surface from a lunar mission, this analysis extends the MMOD community’s insight beyond low Earth orbit into cis-lunar space.
Introduction The Lockheed Martin Orion spacecraft conducted the Artemis I flight around the Moon from November 16 through December 11, 2022. After the flight, an engineer from the NASA Johnson Space Center (JSC) Hypervelocity Impact Technology (HVIT) Group performed a Micrometeoroid and Orbital Debris MMOD analysis using the Bumper 3 risk assessment tool to predict the number of small impacts that would likely have occurred during the mission. Separately, a team from the same group inspected the Orion capsule for hypervelocity impact damage features. The results of the inspection were compared to those of the analysis to aid in improving the analysis, including the environment models. Scope of Work The spacecraft geometry model was created by Lockheed Martin during construction of the Artemis I Orion vehicle based on Computer Aided Design (CAD) models of the vehicle. New hypervelocity impact testing was performed to verify Ballistic Limit Equations (BLEs) used in the analysis to link impactor size and damage to the Thermal Protection System (TPS). The exact trajectory flown was recorded during the flight, including vehicle attitude. This data was used in conjunction with the ORDEM 3.2 and MEM 3 environment modeling tools to create models of particle flux impacting the spacecraft throughout the mission. Meteoroid shower forecast information was also included to account for additional particle flux associated with meteoroid showers. Inspection of the Orion capsule included the Backshell thermal tiles and the tape covering it, windows, fabric thermal materials, and small areas of other materials. Potential MMOD damage found was characterized using various techniques, including optical microscopy, computed tomography scanning, and X-ray spectroscopy. Findings The number of craters found in the Backshell tile, and their size distribution, matches well with the Bumper analysis prediction. Tape, window, and other material impacts recorded similarly align to Bumper analysis predictions. Conclusions and Recommendations This comparison of analysis with inspection of the hardware provides valuable insight into the MMOD environment and how accurately analysis tools assess the impact risk to spacecraft. As this was the first large, non-ablative returned surface from a lunar mission, this analysis extends the MMOD community’s insight beyond low Earth orbit into cis-lunar space.