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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Improving deep learning performance for predicting large-scale geological ${{CO}_{2}}$ sequestration modeling through feature coarsening

Physics-based reservoir simulation for fluid flow in porous media is a numerical simulation method to predict the temporal-spatial patterns of state variables (e.g. pressure p) in porous media, and usually requires prohibitively high computational expense due to its non-linearity and the large number of degrees of freedom (DoF). This work describes a deep learning (DL) workflow to predict the pressure evolution as fluid flows in large-scale 3-dimensional(3D) heterogeneous porous media. In particular, we develop an efficient feature coarsening technique to extract the most representative information and perform the training and prediction of DL at the coarse scale, and further recover the resolution at the fine scale by spatial interpolation. We validate the DL approach to predict pressure field against physics-based simulation data for a field-scale 3D geologic CO 2 sequestration reservoir model. We evaluate the impact of feature coarsening on DL performance, and observe that the feature coarsening not only decreases the training time by >74% and reduces the memory consumption by >75%, but also maintains temporal error 0.63% on average. Besides, the DL workflow provides predictive efficiency with 1406 times speedup compared to physics-based numerical simulation. The key findings from this research significantly improve the training and prediction efficiency of deep learning model to deal with large-scale heterogeneous reservoir models, and thus it can also be further applied to accelerate workflows of history matching and reservoir optimization for close-loop reservoir management.

58 GEOSCIENCES↗
DOE OSTI2021

Sodium tracer measurements of an expanded dense aluminum plasma from e-beam isochoric heating

Spatially and temporally resolved visible absorption spectroscopy is performed on sodium D-lines present as surface contaminants on an expanded dense aluminum plasma plume. An 80-ns FWHM, intense, relativistic electron beam deposits 5.4 J into a 100- μ m-thick Al foil, which isochorically heats and subsequently hydrodynamically expands the material through the warm dense matter state and into a classical-like plasma state, with a coupling parameter of approximately 0.2 and a degeneracy parameter of approximately 270. The Na contamination, carried along with the expanding plume, shows saturated absorption features in the dense Al continuum for λ > 450 nm. X-ray photoelectron spectroscopy and laser-induced breakdown spectroscopy confirm Na is a surface contaminant with an atomic concentration of ~ 0.1 % when interrogating identical foil samples. Additioanlly, a spectroscopic-quality radiation transport model is used to post-process 2D hydrodynamic simulations to interpret the plasma conditions based on the measured Na 3p-3s doublet line profiles. A sodium number density of 3 × 10 15 cm -3 best matches the experimental spectra, which originate from a dense surface plasma with n e = 3.0 ± 0.8 × 10 18 cm -3 .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Structural stability of thin overhanging walls during material extrusion additive manufacturing of thermoset-based ink

Recent developments have enabled material extrusion additive manufacturing of thermoset-based composite inks on the large scale. In addition, printing out-of-plane components is of broad interest to the polymer material extrusion community. Here, we address some of the challenges associated with both large-scale and out-of-plane thermoset material extrusion additive manufacturing by studying the height at which thin overhanging walls collapse. Walls at a range of overhang angles were printed until they collapsed. An optical camera captured the profile of each wall throughout the print, allowing the collapse height to be identified and the geometric fidelity to the programmed angle to be evaluated. Using previously measured rheological properties, predictive models were generated to approximate the collapse height and profile of the deflected walls. First, an analytical model was created to predict the height at which the walls would yield. The analytical model assumes the walls exhibit a perfectly linear profile; however, experiments proved this assumption to be false. Therefore, a finite element simulation was developed to account for the elastic deflection that occurs during printing. The finite element simulation predicts both the yield height and the deflected profile after the deposition of each layer. For the properties of the thermoset ink used here, the yield height predicted by the analytical model and finite element simulation are virtually identical. These predictions match experimental data reasonably well, but minor errors are observed. Accounting for the fully plastic moment appears to explain the small mismatch between experimental data and predictions. Additionally, the finite element simulation provides an excellent prediction of the deflected profile before the wall begins to collapse. Finally, by demonstrating that the collapse height and deflected profile of thin overhanging walls can be predicted, this work illustrates how the soft viscoelastic properties of thermoset-based composite inks limit the scale of a key feature required to print some nonplanar components. It also provides a basis to tailor in-process curing systems to suppress deflection and collapse of thin overhanging walls.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Assessing Uncertainties and Approximations in Solar Heating of the Climate System

In calculating solar radiation, climate models make many simplifications, in part to reduce computational cost and enable climate modeling, and in part from lack of understanding of critical atmospheric information. Whether known errors or unknown errors, the community's concern is how these could impact the modeled climate. The simplifications are well known and most have published studies evaluating them, but with individual studies it is difficult to compare. Here, we collect a wide range of such simplifications in either radiative transfer modeling or atmospheric conditions and assess potential errors within a consistent framework on climate-relevant scales. We build benchmarking capability around a solar heating code (Solar-J) that doubles as a photolysis code for chemistry and can be readily adapted to consider other errors and uncertainties. The broad classes here include: use of broad wavelength bands to integrate over spectral features; scattering approximations that alter phase function and optical depths for clouds and gases; uncertainty in ice-cloud optics; treatment of fractional cloud cover including overlap; and variability of ocean surface albedo. We geographically map the errors in W m -2 using a full climate re-creation for January 2015 from a weather forecasting model. For many approximations assessed here, mean errors are ~2 W m -2 with greater latitudinal biases and are likely to affect a model’s ability to match the current climate state. Combining this work with previous studies, we make priority recommendations for fixing these simplifications based on both the magnitude of error and the ease or computational cost of the fix.

58 GEOSCIENCES↗
DOE OSTI2020

Numerical Investigation of Fuel Property Effects on Mixed-Mode Combustion in a Spark-Ignition Engine

In this research, lean mixed-mode combustion is numerically investigated using computational fluid dynamics (CFD) in a spark-ignition engine. A new E30 fuel surrogate is developed using a neural network model with matched octane numbers. A skeletal mechanism is also developed by automated mechanism reduction and by incorporating a NO x submechanism. A hybrid approach that couples the G-equation model and the well-stirred reactor model is employed for turbulent combustion modeling. The developed CFD model is shown to well predict pressure and apparent heat release rate (AHRR) traces compared with experiment. Two types of combustion cycles (deflagration-only and mixed-mode cycles) are observed. The mixed-mode cycles feature early flame propagation and subsequent end-gas auto-ignition, leading to two distinctive AHRR peaks. The validated CFD model is then employed to investigate the effects of NO x chemistry. The NO x chemistry is found to promote auto-ignition through the residual gas, while the deflagration phase remains largely unaffected. Sensitivity analysis is finally performed to understand effects of fuel properties, including heat of vaporization (HoV) and laminar flame speed (S L ). An increased HoV tends to suppress auto-ignition through charge cooling, while the impact of HoV on flame propagation is insignificant. In contrast, an increased S L is found to significantly promote both flame propagation and end-gas auto-ignition. The promoting effect of S L on auto-ignition is not a direct chemical effect; it is rather caused by an advancement of the combustion phasing, which increases compression heating of the end-gas.

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

Sulphur variations in annually layered stalagmites using benchtop micro-XRF

Variation of sulphur in annually laminated stalagmites can be used to infer the impact of past volcanic activities, anthropogenic pollution, and climate change due to increased bushfire activity. The synchrotron radiation micro-X-Ray fluorescence (SR-XRF) microprobe is a powerful tool to analyse and image sulphur recorded in stalagmites with micrometre resolution. However, access to SR-XRF beamlines can be limited, so researchers must select the most promising stalagmites for imaging. Benchtop micro-XRF is an effective tool for trace elemental analysis of speleothem samples and is a candidate for routine laboratory measurement of sulphur along stalagmite laminae and screening for SR-XRF. Here, this study describes a protocol using matrix-matched standards to measure annual variations of sulphur at trace to percent level along the laminae of two Western Australian stalagmites, one of which already having been analysed using SR-XRF. Parameters that affected quantitation include X-ray tube voltage and current, spot size of the X-ray beam and stalagmite surface roughness and porosity. The use of a 20 μm X-ray spot size provides sub-annual spatial resolution that can be completed in an overnight scan. The features in a 1000 point micro-XRF analysis of sulphur along a 20 mm transect show good consistency with SR-XRF microprobe data. Micro-XRF mapping was also performed to produce chemical images on the stalagmite and compared with Raman and X-ray diffraction (XRD) to confirm that the stalagmite is exclusively calcite, with no aragonite, and that the source of sulphur in the samples was gypsum and anhydrite. Regions of very high sulphur in the micro-XRF maps were found to be artefacts due to diffraction of the incident beam but these could be efficiently removed by using a multiple point statistics approach to produce a clean image suitable for analysis of the laminae. This work shows the potential of micro-XRF for routine analysis of sulphur in stalagmites, and to streamline sample characterisation before SR-XRF imaging.

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

Charge density wave activated excitons in TiSe 2 –MoSe 2 heterostructures

Layered materials enable the assembly of a new class of heterostructures where lattice-matching is no longer a requirement. Interfaces in these heterostructures therefore become a fertile ground for unexplored physics as dissimilar phenomena can be coupled via proximity effects. In this article, we identify an unexpected photoluminescence (PL) peak when MoSe 2 interacts with TiSe 2 . A series of temperature-dependent and spatially resolved PL measurements reveal that this peak is unique to the TiSe 2 –MoSe 2 interface, is higher in energy compared to the neutral exciton, and exhibits exciton-like characteristics. The feature disappears at the TiSe 2 charge density wave transition, suggesting that the density wave plays an important role in the formation of this new exciton. We present several plausible scenarios regarding the origin of this peak that individually capture some aspects of our observations but cannot fully explain this feature. These results therefore represent a fresh challenge for the theoretical community and provide a fascinating way to engineer excitons through interactions with charge density waves.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling ablator grain structure impacts in ICF implosions

High-density carbon is a leading ablator material for inertial confinement fusion (ICF). This and some other ablator materials have grain structure which is believed to introduce very small-scale (~nm) density inhomogeneity. In principle, such inhomogeneity can affect key ICF metrics like fuel compression and yield, by, for example, acting as a seed for instabilities and inducing mix between ablator and fuel. However, assessments of such effects are uncertain due to the difficulty of modeling this small-scale structure in ICF simulations, typically requiring reduced-resolution modeling that scales these features. We present a grain model and show both the impact of de-resolving grains and the complex mixing dynamics such structures can induce. We find that different methods for de-resolving grains can yield both different total deposition of kinetic energy perturbations and different fuel–ablator mixing. We then show a simple-to-implement approach for approximately conserving the deposition of perturbed kinetic energy and demonstrate that, for the present grain model and test cases, this approach yields a reasonably matched time history of mix width between less and more resolved grain models. The simulations here also demonstrate the complex interaction history between grain-induced mixing and instability around the fuel–ablator interface, showing, for example, that the grain-induced perturbations typically trigger instability of conduction-driven density gradients in the DT fuel, enhancing mix penetration early in the acceleration of the shell. Furthermore simulating both microscale and nanoscale grains, we find initial evidence for larger mixing in the microscale case of the present model, despite smaller deposited kinetic energy perturbation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Lightweight jet reconstruction and identification as an object detection task

We apply object detection techniques based on deep convolutional blocks to end-to-end jet identification and reconstruction tasks encountered at the CERN large hadron collider (LHC). Collision events produced at the LHC and represented as an image composed of calorimeter and tracker cells are given as an input to a Single Shot Detection network. The algorithm, named PFJet-SSD performs simultaneous localization, classification and regression tasks to cluster jets and reconstruct their features. This all-in-one single feed-forward pass gives advantages in terms of execution time and an improved accuracy w.r.t. traditional rule-based methods. A further gain is obtained from network slimming, homogeneous quantization, and optimized runtime for meeting memory and latency constraints of a typical real-time processing environment. We experiment with 8-bit and ternary quantization, benchmarking their accuracy and inference latency against a single-precision floating-point. We show that the ternary network closely matches the performance of its full-precision equivalent and outperforms the state-of-the-art rule-based algorithm. Finally, we report the inference latency on different hardware platforms and discuss future applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Design and Evaluation of a Ring Tension Test Grip for Remote Mechanical Testing of Irradiated Tubular Specimens

Here, the ring tension test (RTT) is a mechanical testing method for determining bulk mechanical behavior in the circumferential or hoop direction for tubular materials. The test is especially useful for testing materials with anisotropic mechanical properties, such as zirconium alloys, which are commonly used as nuclear fuel cladding. Anisotropy requires direction-specific testing to determine the hoop strength. Historically, several RTT methods and grips have been used, each method has its strengths and weaknesses, and, in all cases, the measured strength is subject to uncertainty due to variations of the testing geometry and experimental tolerances. Recent analysis has shown that grips with a hemicylindrical mandrel configuration are recommended as the most robust configuration. The two strictest aspects to be controlled are the ability to determine gage region orientation and closely matching the size of the mandrels to the test specimen. This last requirement is particularly challenging when the dimensions of the specimen vary because of environmental effects such as dimensional changes due to irradiation. This paper presents a new RTT grip designed to incorporate this mandrel shape, hold the gage at the desired orientation, be suitable for remote operation in a hot-cell environment, and be adaptable for different sizes or variations in the specimen size. The general description and the unique design features of the test specimen and grips are given in detail. The performance of the grips in mechanical testing, including in a remote hot-cell environment, is also provided.

42 ENGINEERING↗
DOE OSTI2025

A provably stable numerical method for the anisotropic diffusion equation in confined magnetic fields

We present a novel numerical method for solving the anisotropic diffusion equation in magnetic fields confined to a periodic box which is accurate and provably stable. We derive energy estimates of the solution of the continuous initial boundary value problem. A discrete formulation is presented using operator splitting in time with the summation by parts finite difference approximation of spatial derivatives for the perpendicular diffusion operator. Weak penalty procedures are derived for implementing both boundary conditions and parallel diffusion operator obtained by field line tracing. We prove that the fully-discrete approximation is unconditionally stable. Discrete energy estimates are shown to match the continuous energy estimate given the correct choice of penalty parameters. A nonlinear penalty parameter is shown to provide an effective method for tuning the parallel diffusion penalty and significantly minimises rounding errors. Several numerical experiments, using manufactured solutions, the “NIMROD benchmark” problem and a single island problem, are presented to verify numerical accuracy, convergence, and asymptotic preserving properties of the method. Finally, we present a magnetic field with chaotic regions and islands and show the contours of the anisotropic diffusion equation reproduce key features in the field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗
DOE OSTI2021

Multi-spatio-temporal scales PIV in a turbulent buoyant jet discharging in a linearly stratified environment

Time-resolved particle image velocimetry is implemented with a camera array and several laser sheets; this results in a multi-spatio-temporal scale system that is modular and flexible. The setup is optimized to capture global flow features, while locally resolving in space and time near the Kolmogorov scale. The apparatus relies extensively on machine vision CMOS cameras; they are inexpensive and stream to computer hard drive with virtually continuous time-resolved records (up to one hour for the current system). This leads to statistically converged data and also helps in minimizing down time between experimental runs. Details of the implementation and design of experiment are reported. The system instruments a vertical buoyant jet discharging in a linearly stratified environment. Refractive index matched aqueous solutions enable precise optical deployment. The density difference is 3% and the fluids have similar dynamic viscosity. The jet Reynolds number is 2.00 x 10 4 and is above the mixing transition. Such flows are typically challenging to instrument and few velocity field data are available to date. The velocity statistics are reported as well as first insights gained from the campaign.

42 ENGINEERING↗
DOE OSTI2021

Combining Spectroscopic Techniques to Determine the Optical Constants of Powdered Lactose

A method for deriving the optical constants (n/k) of organic powdered materials using pressed pellets in the mid-infrared spectral range is introduced that combines variable angle spectroscopic ellipsometry and transmission spectroscopy. The approach is applied to lactose, in which three different forms of pellets were pressed and measured: A pure lactose pellet and a mixed lactose/KBr pellet with a large analyte percentage were used for ellipsometric measurements, and a KBr transmission pellet with only a small analyte percentage were used for transmission measurements. The transmission data provide an initial set of oscillators and improve the spectral fitting of weak absorption features (k<0.01). Ellipsometric data for the pure and mixed pellets are then fit simultaneously to derive the final n/k values for lactose from 6000-400 cm-1. An alternative method just using the ellipsometric data from the mixed pellet and the transmission data is also presented and shows good agreement with the multi-sample analysis, providing a simpler method for powders that do not press easily into pure pellets. Finally, the derived optical constants are used to model the reflectance data, demonstrating a good match with the measured reflectance spectra if non-idealities are included.

Yokosuk, Michael O.↗
DOE OSTI2025

An In Situ Feed Monitoring System for Molten Salt Reactors with Fast Neutron Energy Spectrum Molten Salt Reactor Applications

Molten salt reactors (MSRs) are one of the six promising advanced reactor technologies selected for further research and development by the Generation IV International Forum. More than twenty MSR designs are actively being developed around the world. Several of these designs are liquid-fueled and intended for operation within the fast neutron energy spectrum.1 National regulations will require liquid-fueled MSRs to control and account for nuclear material within licensed facilities. Additionally, states with comprehensive safeguards agreements with the International Atomic Energy Agency (IAEA) are obligated to declare nuclear material quantities within facilities. In return, the IAEA Department of Safeguards independently verifies these quantities and provides assurance that the nuclear material and facility are being used only for peaceful purposes. One key distinction of liquid-fueled MSRs compared with other types of reactors is that in portions of the facility, the nuclear material is in bulk form rather than discrete items. Traditional nuclear material accounting techniques such as physical item counting and verification of serial numbers on fresh fuel assemblies do not translate directly to all process streams within liquid-fueled reactors. Liquid-fueled MSRs are typically designed with low excess reactivity. This feature provides safety benefits but also means that most MSRs require the addition of makeup fuel salt while a reactor is operational. The nuclear material in the initial fuel salt and in any makeup fuel salt must be quantified. Additionally, distinct nuclear material diversion and reactor misuse scenarios form the basis of the detection methods and monitoring systems developed for liquid-fueled MSRs. For example, the IAEA provides assurance that fuel salt containing nuclear material is not being diverted from the system, that the feed salt matches the reported actinide concentrations and uranium enrichment, and that no additional fertile material is being introduced into the system. Measurement systems currently used for nuclear material control and accounting are not directly applicable to achieving MSR safeguards goals. This paper concerns a system being designed to account for the nuclear material added to liquid-fueled MSRs and monitor for diversion and misuse scenarios related to MSR feed systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Computing the Properties of Matter with Leadership Computing Resources (Closeout Report for DE-SC0018121)

In order to add more capabilities to Halide, we have designed a new framework called Tiramisu and integrated this framework into Halide. Since Tiramisu enables Halide to target heterogeneous architectures, our development efforts have been refocused on Tiramisu. Most high-performance computer systems today are complex and increasingly heterogeneous; they may have CPUs, GPUs and FPGAs. Achieving best performance requires taking full advantage of all these different architectures. To address this issue, we have designed Tiramisu, an optimization framework that enables Halide (and other DSLs) to target heterogeneous architectures. Tiramisu is an optimization framework that takes as input a high level, architecture-independent representation of code and a set of scheduling and data mapping commands that guide code transformation. The input can either be generated by a domain-specific language (DSL) compiler such as Halide or directly written by a programmer. Tiramisu then applies the user-specified code and data-layout transformations and generates an architecture-specific, low-level intermediate representation (IR) that takes advantage of modern architectural features such as multicore parallelism, non-uniform memory (NUMA) hierarchies, clusters, and accelerators like GPUs and FPGAs. We integrated Tiramisu within Halide and implemented a representative set of benchmarks to evaluate this integration. Tiramisu is now open source and is available for public use (http://tiramisu-compiler.org/). A paper about Tiramisu was published, it shows that Tiramisu extends Halide with many new capabilities and that Tiramisu can generate efficient code for multicores, GPUs, FPGAs and distributed heterogeneous systems. The performance of code generated by the Tiramisu backends matches or exceeds hand optimized reference implementations. For example, the multicore backend matches the highly optimized Intel MKL library on many kernels and shows speedups reaching 4x over the original Halide. In addition to making Tiramisu more robust, we have used Tiramisu to implement a set of representative tensor operation for constructing baryon building blocks required for multi baryon contractions in LQCD. In order to implement this code, we needed to generalize Tiramisu in two ways: first we needed to support indirect array accesses, and second, we needed to add support for complex numbers to Tiramisu. The code generated by Tiramisu is 6x faster than the reference code. Our efforts towards an MPI based multi-node version of tiramisu have matured and the resulting code scales well on multiple nodes (tests up to 512 KNL nodes have been undertaken).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Binary pseudo-random array (BPRA) for inspection and calibration for cylindrical wavefront interferometry

High-accuracy metrology is vitally important in manufacturing ultra-high-quality free-form mirrors designed to manipulate X-ray light with nanometer-scale wavelengths. However, surface topography measurements are instrument dependent, and without the knowledge of how the instrument performs under the practical usage conditions, the measured data contain some degree of uncertainty. Binary Pseudo Random Array (BPRA) “white noise” artifact are effective and useful for characterizing the Instrument Transfer Function (ITF) of surface topography metrology tools and wavefront measurement instrument. BPRA artifact contains features with all spatial frequencies in the instrument bandpass with equal weight. As a result, power spectral density of the patterns has a deterministic white-noise-like character that allows direct determination of the ITF with uniform sensitivity over the entire spatial frequency range. The application examples include electron microscopes, x-ray microscopes, interferometric microscopes, and large field-of-view Fizeau Interferometers. Furthermore, we will introduce the application of BPRA method to characterizing the ITF of Cylindrical Wavefront Interferometry (CWI), by developing the BPRA artifact which matches the radius of curvature of the cylindrical wavefront. The data acquisition and analysis procedures for different applications of the ITF calibration technique developed are also discussed.

Munechika, K↗
DOE OSTI2020

A New CIERRA Gridded Product Climatology for LIS/OTD

The GLM-CIERRA processing generates two products: A level-2 cluster feature dataset that merges flashes that should have been a single flash following the clustering algorithm flash definition (for GLM, this is due to the LCFA thresholds); A set of level-3 gridded products including Flash Extent Density, Convective Probability, etc. The CIERRA Level-3 products are generated on a 0.1 degree grid. This is suboptimal given the spatial variations in GLM pixel size AND the size of gridpoints in the output grid. As a stepping-stone towards developing improved GLM-CIERRA grids, I am testing pixel matching techniques on the LIS/OTD data. The goal is to maintain accuracy while vastly improving computational efficiency. The CIERRA reclustering codes are also being applied to LIS / OTD to merge flashes split by the “first fit” clustering technique. The end result will be standardized grids at the nominal resolution of each instrument (5 km for LIS, 10 km for OTD) that take into account the pixel geometry for each event that comprises a given reclustered flash.

54 ENVIRONMENTAL SCIENCES↗