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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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Properly combining optical design with 3-by-3 element mask reduces number of required computations by factor of as much as 100. Spatial and spatial-frequency responses obtained in system of combination of optical design and signal-processing algorithm. Closely approximate difference-of-Gaussian-function response.
Purpose: Multileaf collimator (MLC)-driven conformal radiotherapy modalities [e.g., such as intensity-modulated radiotherapy (IMRT), intensity-modulated arc therapy, and stereotactic body radiotherapy] are more subject to delivery errors and dose calculation inaccuracies than standard modalities. Fluence monitoring during treatment delivery could reduce such errors by allowing an independent interface to quantify and assess measured difference between the delivered and planned treatment administration. We developed an optical attenuation-based detector to monitor fluence for the on-line quality control of radiotherapy delivery. The purpose of the current study was to develop the theoretical background of the invention and to evaluate the detector's performance both statistically and in clinical situations. Methods: We aligned 60 27-cm scintillating fibers coupled to a photodetector via clear optical fibers in the direction of motion of each of the 60 leaf pairs of a 120 leaves Millenium MLC on a Varian Clinac iX. We developed a theoretical model to predict the intensity of light collected on each side of the scintillating fibers when placed under radiation fields of varying sizes, intensities, and positions. The model showed that both the central position of the radiation field on the fiber (x{sub c}) and the integral fluence passing through the fiber ({Phi}{sub int}) could be assessed independently in a single measurement. We evaluated the performance of the prototype by (1) measuring the intrinsic variation of the measured values of x{sub c} and {Phi}{sub int}, (2) measuring the impact on the measured values of x{sub c} and {Phi}{sub int} of random leaf positioning errors introduced into IMRT fields, and (3) comparing the predicted values of x{sub c} and {Phi}{sub int} calculated with the treatment planning software to the measured values of x{sub c} and {Phi}{sub int} in order to assess the predictive effectiveness of the developed theoretical model. Results: We observed a very low intrinsic dispersion, dominated by Poisson statistics, for both x{sub c} (standard deviations of less than 1 mm) and {Phi}{sub int} (standard deviations of less than 0.20%). When confronted with random leaf positioning errors from IMRT segments, {Phi}{sub int} was highly sensitive to single leaf positioning errors as small as 1 mm at isocenter, while x{sub c} was sensitive to leaf pair translation errors of at least 2 mm at isocenter. Owing to the uncertainties in the doses calculated in regions of high perpendicular dose gradients, the measured values of x{sub c} and {Phi}{sub int} deviated from the predicted values of x{sub c} and {Phi}{sub int} by a mean of 1.3 mm and 2.6%, respectively. Conclusion: Our study showed that an optical attenuation-based detector can be used to effectively monitor integral fluence during radiotherapy delivery. The performance of such a system would enable real-time quality control of the incident fluence in current MLC-driven treatments such as IMRT and future adaptive radiotherapy procedures where new treatment plans will have to be delivered without passing thru the current standard quality control chain.
Here in this work, we apply an effective discrete phase front focusing method to control the coherent combining and temporal compression of laser pulses by means of nonlinear multicore fibers. We numerically demonstrate the possibility of combining almost entirely the input optical pulses injected in all cores, into the central core of a hexagonal lattice multicore fiber. We investigate the optimal operational conditions for the most effective pulse combining and analyze the influence of a positive input pulse temporal chirp and spatial phase modulation. We demonstrate that a pulse, which has been focused into an arbitrary core of the fiber, also undergoes temporal compression.
This work presents a comparative analysis of the various signal processing techniques used in the Brillouin gain spectrum (BGS) peak estimation. Traditional fitting methods such as Lorentzian curve fitting (LCF) are slow and less effective in noisy data. PCA-based methods were tested on the experimental data: A Euclidian distance-based approach, and a probabilistic deep neural network (PDNN) based approach, both using 5 principal components to represent a single BGS. Both methods significantly reduce computational time with respect to LCF, whereas PDNN offers uncertainty insights along with the parameter value. Measuring a range of temperatures, analyzing accuracy, and speed, it can be concluded that PCA trained PDNN outperforms other methods, and appears to be helpful in scenario where large datasets are generated.
A system utilizing a digital computer for acquiring, storing and evaluating crystal images. The system includes a video camera (12) which produces a digital output signal representative of a crystal specimen positioned within its focal window (16). The digitized output from the camera (12) is then stored on data storage media (32) together with other parameters inputted by a technician and relevant to the crystal specimen. Preferably, the digitized images are stored on removable media (32) while the parameters for different crystal specimens are maintained in a database (40) with indices to the digitized optical images on the other data storage media (32). Computer software is then utilized to identify not only the presence and number of crystals and the edges of the crystal specimens from the optical image, but to also rate the crystal specimens by various parameters, such as edge straightness, polygon formation, aspect ratio, surface clarity, crystal cracks and other defects or lack thereof, and other parameters relevant to the quality of the crystals.
The problem of detecting rocket plumes at thermospheric altitudes with satellite-borne submillimeter-wave radiometers is examined theoretically. To estimate the sizes of plume signatures contrasted against a 250-K earth background or in self-emission against the cold sky, a computer program has been developed to predict plume brightness temperatures and optical depths of rotational lines of plume molecular constituents (e.g., H2O) as a function of distance from the nozzle. The methods employed in the computations are described in general terms, and examples are presented to indicate that detectable H2O signatures extending to several thousand nozzle diameters should exist at plume altitudes above 250 km.
The use of the Convex Computer Corporation supercomputers for flight simulation is discussed focusing on a real-time input/output system for supporting the flight simulation. The flight simulation computing system is based on two single processor control data corporation CYBER 175 computers, coupled through extended memory. The Advanced Real-Time Simulation System for digital data distribution and signal conversion is a state-of-the-art, high-speed fiber-optic-based, ring network system which is based on the computer automated measurement and control technology.
A real-time two-dimensional hybrid processor consisting of a coherent optical system, an optical/digital interface, and a PDP-11/15 control minicomputer is described. The input electrical-to-optical transducer is an electron-beam addressed potassium dideuterium phosphate (KD2PO4) light valve. The requirements and hardware for the output optical-to-digital interface, which is constructed from modular computer building blocks, are presented. Initial experimental results demonstrating the operation of this hybrid processor in phased-array radar data processing, synthetic-aperture image correlation, and text correlation are included. The applications chosen emphasize the role of the interface in the analysis of data from an optical processor and possible extensions to the digital feedback control of an optical processor.
In this work, we demonstrate the key features of an interference cathode using both simulations and experiments. We deposit Cs 3 Sb photocathodes on Ag to produce an interference enhanced photocathode with 2–5× quantum efficiency (QE) enhancement using a robust procedure that requires only a smooth metal substrate and QE monitoring during growth. We grow both an interference cathode (Ag substrate) and a typical photocathode (Si reference substrate) simultaneously to confirm that the effects are due to optical interactions with the substrate rather than photocathode composition or surface electron affinity differences. Growing the cathodes until the QE converges shows both the characteristic interference peaks during growth and the identical limiting case where the cathode is “infinitely thick,” in agreement with simulations. We also grow a cathode until the QE on Ag peaks and then stop the growth, demonstrating broadband QE enhancement.
A computational model based on the axisymmetric, thin-layer Navier-Stokes equations is developed to predict the convective, radiation and conductive heat transfer in high temperature space nuclear reactors. An implicit-explicit, finite volume, MacCormack method in conjunction with the Gauss-Seidel line iteration procedure is utilized to solve the thermal and fluid governing equations. Simulation of coolant and propellant flows in these reactors involves the subsonic and supersonic flows of hydrogen, helium and uranium tetrafluoride under variable boundary conditions. An enthalpy-rebalancing scheme is developed and implemented to enhance and accelerate the rate of convergence when a wall heat flux boundary condition is used. The model also incorporated the Baldwin and Lomax two-layer algebraic turbulence scheme for the calculation of the turbulent kinetic energy and eddy diffusivity of energy. The Rosseland diffusion approximation is used to simulate the radiative energy transfer in the optically thick environment of gas core reactors. The computational model is benchmarked with experimental data on flow separation angle and drag force acting on a suspended sphere in a cylindrical tube. The heat transfer is validated by comparing the computed results with the standard heat transfer correlations predictions. The model is used to simulate flow and heat transfer under a variety of design conditions. The effect of internal heat generation on the heat transfer in the gas core reactors is examined for a variety of power densities, 100 W/cc, 500 W/cc and 1000 W/cc. The maximum temperature, corresponding with the heat generation rates, are 2150 K, 2750 K and 3550 K, respectively. This analysis shows that the maximum temperature is strongly dependent on the value of heat generation rate. It also indicates that a heat generation rate higher than 1000 W/cc is necessary to maintain the gas temperature at about 3500 K, which is typical design temperature required to achieve high efficiency in the gas core reactors. The model is also used to predict the convective and radiation heat fluxes for the gas core reactors. The maximum value of heat flux occurs at the exit of the reactor core. Radiation heat flux increases with higher wall temperature. This behavior is due to the fact that the radiative heat flux is strongly dependent on wall temperature. This study also found that at temperature close to 3500 K the radiative heat flux is comparable with the convective heat flux in a uranium fluoride failed gas core reactor.
Real-time tracking of wildfires and smoke is crucial for effective response, minimizing damage, protecting lives, and efficiently managing resources during fire emergencies. We develop a web-based AI-powered pipeline that detects wildfires in aerial video and estimates deployment-relevant behavior metrics, including cumulative burned area, burned-area growth rate, fire spread direction, and smoke dispersion. The system combines a YOLO-based detector with YCbCr-based fire segmentation, HSV-based smoke segmentation, Farneback optical flow, and centroid-based spatiotemporal tracking. Using ground sampling distance (GSD), pixel-level fire masks are converted to physical burned-area measurements by correlating fire pixel counts with camera altitude and tilt angle. We benchmark YOLO variants and non-YOLO baselines (GoogLeNet, CNN, DBN, Autoencoder, U-Net, and AlexNet) on the IEEE FLAME dataset and a newly created aerial frame dataset, Wildfire-DB. Cross-dataset evaluation uses a strict threshold-transfer protocol: decision thresholds are selected on FLAME validation and transferred unchanged to Wildfire-DB to quantify generalization under domain shift. YOLOv6 achieves the strongest cross-dataset frame-level fire detection on Wildfire-DB (ROC-AUC 0.8200, PR-AUC 0.8044, and transferred-threshold F1 0.7596). For tracking-oriented deployment requiring oriented localization, YOLO11-OBB provides the most reliable cross-dataset behavior among OBB-capable models while remaining computationally feasible. To analyze the feasibility of UAV deployment, we further measure inference efficiency using synchronized GPU and CPU power logs on a fixed workload of 1569 frames. YOLO-family models process the video in 5.73–12.47 seconds with net energy of 1247.28–1775.39 J, substantially lower latency and energy than heavier classification and reconstruction baselines. Overall, model optimality depends on operational objectives: YOLOv6 is best for cross-dataset detection robustness, whereas YOL...
Various applications—including brain-like computing and on-chip artificial vision—increasingly demand a combination of electronic and photonic techniques. However, integrating both approaches on a single chip is challenging, and solutions typically rely on disparate components with power-hungry signal conversions. Here, in this paper, we report electro-optical Mott neurons that combine visible light emission with electrical threshold switching, as well as neuron-like oscillations. The devices are based on thin films of sputtered niobium dioxide (NbO 2 ), a Mott insulator–metal transition material, operating at room temperature and emitting light that peaks around 810 nm. Operando measurements reveal an electronic origin to the light emission: charge carrier relaxation initiated by high-field transport in the NbO 2 . Our devices combine electrical and optical functions within a single material, thereby expanding the options available for future artificial intelligence hardware.
Laser powder bed fusion (LPBF) is the most widely used process for metal additive manufacturing (AM), particularly where complex geometries provide performance advantages unattainable with traditional manufacturing techniques. However, LPBF is highly sensitive to innate variability in both the powder spreading and fusion steps, often leading to defects such as pores that are difficult to detect yet significantly impair component mechanical properties and fatigue life. This thesis presents a range of novel instruments enabling both precise assessment of powder layer characteristics and in-situ thermal metrology of metal AM to advance the quality control of LPBF. First, leveraging a custom X-ray microscope and a radiation-transport model developed through this work, transmission X-ray imaging is used to study spreading of thin metal powder layers. Effective layer depth is directly mapped at a process-relevant size scale, surpassing optical techniques that can only estimate local deposition from layer surface topography. Layer packing density and quality are shown to be influenced by powder flowability and particle size relative to nominal powder layer thickness. Layer quality is additionally connected to the geometry of the spreading implement and its velocity. This technique and its presented findings enable pairing feedstocks with spreading strategies that create layers with consistent packing density and uniformity. Second, a twofold approach is employed to optically interrogate the laser fusion step of LPBF for observing signatures of defect formation. Aperture division multiplexing is conceptualized, providing for simultaneous laser delivery and high-fidelity infrared (IR) process monitoring through a common optic. In-situ microscopy at 50 μm spatial resolution and at mid-wave IR wavelengths is proven readily achievable with the first purpose-built optic of this type. Next, a bespoke imaging spectrometer, along with a temperature-emissivity separation technique, is used to retrieve accurate process temperatures over a 1000 K range. Data from these instruments are correlated to porosity as fine as 4.3 μm in two LPBF test artifacts, as verified using computed tomography (CT), establishing the viability of robust optically-based component qualification.
How do you create the largest 3-D map of the universe? It’s as easy as teaching 5,000 robots how to “dance.” DESI, the Dark Energy Spectroscopic Instrument, is an experiment that will target millions of distant galaxies by automatically swiveling fiber-optic positioners (the robots) to point at them and gather their light. Scientists working at Berkeley Lab are assembling this array of robots and their related electronics – together representing into a series of 10 wedge-shaped petals that will be fitted together to form a circular focal plane. The focal plane will be mounted near the top of the Mayall Telescope at Kitt Peak National Observatory near Tucson, Arizona. This 3-minute video features interviews with two Berkeley Lab scientists: Joseph Silber, Focal Plane Lead Engineer, DESI Claire Poppett, Lead Fiber Scientist for DESI Video Credit: Marilyn Chung/Berkeley Lab
Auger electron spectroscopy and ellipsometry were applied in order to measure the optical constants and study the surface chemistry of vapor-deposited Al films and high-purity bulk Al surfaces in situ under vacuum. The optical constants measured were compared with the extinction coefficient computed by the free-electron theory. The contamination of the clean Al surface was in the form of a metal oxide film. Auger electron spectroscopic measurements were used to establish the relationship between the Auger peaks of O (513 eV) and aluminum oxide (53 eV) and changes in the measured optical phase and film thickness. The free path length of the Al Auger electrons (67 eV) in the oxide film was determined, and it was shown that the amplitude of these peaks is a linear function of film thickness down to 0.6 A.
Under the support of the aforementioned DOE Grant, we have made two fundamental contributions to atmospheric and climate sciences: (1) Develop an efficient 3-D radiative transfer parameterization for application to intense and intricate inhomogeneous mountain/snow regions. (2) Innovate a stochastic parameterization for light absorption by internally mixed black carbon and dust particles in snow grains for understanding and physical insight into snow albedo reduction in climate models. With reference to item (1), we divided solar fluxes reaching mountain surfaces into five components: direct and diffuse fluxes, direct- and diffuse-reflected fluxes, and coupled mountain-mountain flux. “Exact” 3D Monte Carlo photon tracing computations can then be performed for these solar flux components to compare with those calculated from the conventional plane-parallel (PP) radiative transfer program readily available in climate models. Subsequently, Parameterizations of the deviations of 3D from PP results for five flux components are carried out by means of the multiple linear regression analysis associated with topographic information, including elevation, solar incident angle, sky view factor, and terrain configuration factor. We derived five regression equations with high statistical correlations for flux deviations and successfully incorporated this efficient parameterization into WRF model, which was used as the testbed in connection with the Fu-Liou-Gu PP radiation scheme that has been included in the WRF physics package. Incorporating this 3D parameterization program, we conducted simulations of WRF and CCSM4 to understand and evaluate the mountain/snow effect on snow albedo reduction during seasonal transition and the interannual variability for snowmelt, cloud cover, and precipitation over the Western United States presented in the final report. With reference to item (2), we developed in our previous research a geometric-optics surface-wave approach (GOS) for the computation of light absorption and scattering by complex and inhomogeneous particles for application to aggregates and snow grains with external and internal mixing structures. We demonstrated that a small black (BC) particle on the order of 1 μm internally mixed with snow grains could effectively reduce visible snow albedo by as much as 5–10%. Following this work and within the context of DOE support, we have made two key accomplishments presented in the attached final report.
The vibrational properties, electronic structures and optical properties of novel carbon allotropes, such as monolayer penta-graphene (PG), double-layer PG and T12-carbon, were studied by first-principles calculations. Results of phonon calculations demonstrate that these exotic carbon allotropes are dynamically stable. The bulk T12 phase is an indirect-gap semiconductor having a quasiparticle (QP) bandgap of ~5.19 eV. When the bulk material transforms to a two-dimensional (2D) phase, the monolayer and double-layer PG become quasi-direct gap semiconductors with smaller QP bandgaps of ~4.48 eV and ~3.67 eV, respectively. Furthermore, the partial charge density analysis indicates that the 2D phases retain part of the electronic characteristics of the T12 phase. The linear photon energy-dependent dielectric functions and related optical properties including refractive index, extinction coefficient, absorption spectrum, reflectivity, and energy-loss spectrum were also computed and discussed. Additionally, the chemical stability of monolayer PG and the electronic and optical properties of double-side hydrogenated monolayer PG were also investigated. Furthermore, the results obtained from our calculations are beneficial to practical applications of these exotic carbon allotropes in optoelectronics and electronics.
This study aims to isolate interactions between plies and tows and reveal fundamental physics involved in transverse impact on fiber-reinforced composite (FRC) structures. Composite strips were sectioned from large panels and characterized by optical photography, three-dimensional synchrotron X-ray computed tomography, and scanning electron microscopy (SEM). Each strip was impacted perpendicularly by a right circular cylinder (RCC) projectile at a velocity ranging from ~ 150 to 600 m/s. The global strip behavior, as well as localized deformation and failure of the strip near the projectile corner, were both captured by high-speed optical imaging. S-Glass FRC strips were observed to fail in tension ahead of the RCC projectiles’ flat surfaces while Kevlar® FRC strips fractured at the projectile corners. The concept of critical velocity region previously used for impact on yarns was introduced to define different failure modes of each composite strip type. The strip damage extent was found to increase with the impact velocity and reach the maximum at the upper limit of the critical velocity region. Above the critical velocity region, the damage extent decreased with impact velocity. Wave propagations and load histories in the composite strips during impact were quantified and compared with Smith’s theory. Finally, critical velocities of single fibers, yarns, and composite strips and ballistic limits of single-ply and multi-ply composite panels were compared to provide insight into the design of impact-resistant fabrics and composites.