Zero Padding with FFT Analysis of PDV Data
Presentation for a WebEx meeting on September 15 sponsored by Jose Sinibaldi's Work in Progress Seminars.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
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Results for “zero padding”
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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Deep learning-based spatio-temporal estimate of greenhouse gas emissions using satellite data
Accurate estimation of greenhouse gases (GHGs) emissions is very important for developing mitigation strategies to climate change by controlling and reducing GHG emissions. This project aims to develop multiple deep learning approaches to estimate anthropogenic greenhouse gas emissions using multiple types of satellite data. NO2 concentration is chosen as an example of GHGs to evaluate the proposed approach. Two sentinel satellites (sentinel-2 and sentinel-5P) provide multiscale observations of GHGs from 10-60m resolution (sentinel-2) to ~kilometer scale resolution (sentinel-5P). Among multiple deep learning (DL) architectures evaluated, two best DL models demonstrate that key features of spatio-temporal satellite data and additional information (e.g., observation times and/or coordinates of ground stations) can be extracted using convolutional neural networks and feed forward neural networks, respectively. In particular, irregular time series data from different NO 2 observation stations limit the flexibility of long short-term memory architecture, requiring zero-padding to fill in missing data. However, deep neural operator (DNO) architecture can stack time-series data as input, providing the flexibility of input structure without zero-padding. As a result, the DNO outperformed other deep learning architectures to account for time-varying features. Overall, temporal patterns with smooth seasonal variations were predicted very well, while frequent fluctuation patterns were not predicted well. In addition, uncertainty quantification using conformal inference method is performed to account for prediction ranges. Overall, this research will lead to a new groundwork for estimating greenhouse gas concentrations using multiple satellite data to enhance our capability of tracking the cause of climate change and developing mitigation strategies.
54 ENVIRONMENTAL SCIENCES↗
A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining
Transformers are considered one of the most important deep learning models since 2018, in part because it establishes state-of-the-art (SOTA) records and could potentially replace existing Deep Neural Networks (DNNs). Despite the remarkable triumphs, the prolonged turnaround time of Transformer models is a widely recognized roadblock. The variety of sequence lengths imposes additional computing overhead where inputs need to be zero-padded to the maximum sentence length in the batch to accommodate the parallel computing platforms. This paper targets the field-programmable gate array (FPGA) and proposes a coherent sequence length adaptive algorithm–hardware co-design for Transformer acceleration. Particularly, we develop a hardware-friendly sparse attention operator and a length-aware hardware resource scheduling algorithm. The proposed sparse attention operator brings the complexity of attention-based models down to linear complexity and alleviates the off-chip memory traffic. The proposed length-aware resource hardware scheduling algorithm dynamically allocates the hardware resources to fill up the pipeline slots and eliminates bubbles for NLP tasks. Experiments show that our design has very small accuracy loss and has 80.2 × and 2.6 × speedup compared to CPU and GPU implementation, and 4 × higher energy efficiency than state-of-the-art GPU accelerator optimized via CUBLAS GEMM.
Peng, Hongwu↗
Synthetic Atmospheric River Ensembles Generated by Deep-AR
This dataset contains 35,850 synthetic landfalling atmospheric river (AR) realizations generated by the Deep-AR two-stage deep-learning framework over the Northeast Pacific and U.S. West Coast. The archive contains 25 stochastic ensemble members for each of 1,434 held-out observed seed events. Each synthetic realization is initialized from conditions 48 hours before the corresponding observed AR landfall and is generated autoregressively at 6-hour intervals over a 144-hour period. Deep-AR combines a deterministic residual network (ResNet) that advances the large-scale atmospheric state with a Wasserstein generative adversarial network (WGAN) that produces stochastic, high-resolution fields. Each HDF5 file contains 0.25° gridded synthetic integrated vapor transport components (qu, qv), 10 m wind components (u10, v10), and 6-hour accumulated precipitation on a common 200 × 480 grid. The files also include coordinate and datetime arrays. This dataset supports AR hazard analysis, ensemble-based uncertainty characterization, precipitation-extremes research, and regional stress testing. Synthetic files follow the naming convention deepar.model.YYYYMMDD.HHMMSS.vNN.h5. YYYYMMDD.HHMMSS identifies the UTC initial-condition timestamp, which occurs 48 hours before the diagnosed observed landfall, and vNN identifies the zero-padded ensemble member, ranging from v01 through v25. Each synthetic file can be paired with its corresponding observed file by matching the initial-condition timestamp. The paired observed file follows the naming convention deepar.obs.YYYYMMDD.HHMMSS.h5 and is available in the separately registered oracle/deepar.obs dataset at https://wdh.energy.gov/ds/oracle/deepar.obs (DOI: https://doi.org/10.21947/3377671).
17 WIND ENERGY↗
FFT-local gravimetric geoid computation
Model computations show that changes of sampling interval introduce only 0.3 cm changes, whereas zero padding provides an improvement of more than 5 cm in the fast Fourier transformation (FFT) generated geoid. For the Global Positioning System (GPS) survey of Franklin County, Ohio, the parameters selected as a result of model computations, allow large reduction in local data requirements while still retaining the cm accuracy when tapering and padding is applied. The results are shown in tables.
Nagy, Dezso↗
Advanced Signal Processing Methods Applied to Digital Mammography
The work reported here is on the extension of the earlier proposal of the same title, August 1994-June 1996. The report for that work is also being submitted. The work reported there forms the foundation for this work from January 1997 to September 1997. After the earlier work was completed there were a few items that needed to be completed prior to submission of a new and more comprehensive proposal for further research. Those tasks have been completed and two new proposals have been submitted, one to NASA, and one to Health & Human Services WS). The main purpose of this extension was to refine some of the techniques that lead to automatic large scale evaluation of full mammograms. Progress on each of the proposed tasks follows. Task 1: A multiresolution segmentation of background from breast has been developed and tested. The method is based on the different noise characteristics of the two different fields. The breast field has more power in the lower octaves and the off-breast field behaves similar to a wideband process, where more power is in the high frequency octaves. After the two fields are separated by lowpass filtering, a region labeling routine is used to find the largest contiguous region, the breast. Task 2: A wavelet expansion that can decompose the image without zero padding has been developed. The method preserves all properties of the power-of-two wavelet transform and does not add appreciably to computation time or storage. This work is essential for analysis of the full mammogram, as opposed to selecting sections from the full mammogram. Task 3: A clustering method has been developed based on a simple counting mechanism. No ROC analysis has been performed (and was not proposed), so we cannot finally evaluate this work without further support. Task 4: Further testing of the filter reveals that different wavelet bases do yield slightly different qualitative results. We cannot provide quantitative conclusions about this for all possible bases without further support. Task 5: Better modeling does indeed make an improvement in the detection output. After the proposal ended, we came up with some new theoretical explanations that helps in understanding when the D4 filter should be better. This work is currently in the review process. Task 6: N/A. This no longer applies in view of Tasks 4-5. Task 7: Comprehensive plans for further work have been completed. These plans are the subject of two proposals, one to NASA and one to HHS. These proposals represent plans for a complete evaluation of the methods for identifying normal mammograms, augmented with significant further theoretical work.
Stauduhar, Richard P.↗
Toward High-Quality X-59 Sonic Thump Measurements
Brigham Young University has been investigating best practices for recommendation to NASA in upcoming X-59 sonic thump measurements. This preparatory work has focused both on obtaining high-fidelity data and standardizing signal analysis techniques for sonic thumps. Included in the research are topics such as whether to use a ground-based or elevated microphone, how to use low-noise microphones and still recover high-fidelity data at low frequencies, and estimating the uncertainty in a given measurement due to local atmospheric turbulence effects. Also included is a study of windowing techniques, zero padding, and the removal of high-frequency ambient noise contamination.
sonic boom↗
Completion design improvement using a deep convolutional network
Maximizing stimulated natural and hydraulic fracture network is one of the primary hydraulic fracturing concerns for economic production from a horizontal shale gas well. Geomechanical facies and preexisting fractures in each stage are identified based on similarities in formation characteristics to optimize the locations of perforation clusters. This often requires analyzing large volumes of drilling, Logging While Drilling (LWD) and Measurement While Drilling (MWD) data. In this paper, we develop a methodology that calculates the mechanical specific energy (MSE) using real-time drill string acceleration signals directly from its definition. High resolution vibration signals have been collected using a tri-axial accerlometer, which was an auxiliary tool included in acoustic borehole imager. This technique provides a cost-efficient solution for engineered completion design. Furthermore, we adopt deep Convolutional Neural Network (CNN) with signal processing to build a data pipeline that effectively extracts patterns from dynamic acceleration signals for rock lateral MSE classification. First, we apply discrete wavelet transform and Short-Time Fourier Transform (STFT) for signal denoising and pattern recognition. Then we construct an image dataset using multi-scale image fusion at pixel level from 3 sensor channels, including axial, lateral acceleration spectrograms and zero-padded revolutions per minute (RPM). The resulted RGB image dataset includes 4,000 images of 5 MSE ranges with various rock strength conditions. Our results demonstrate that the proposed deep learning model can achieve more than 90% classification accuracy. The deep learning results, as a reference source, were applied in selected Marcellus Shale Energy and Environmental Lab (MSEEL) wells engineered completion located in the Marcellus shale gas site.
03 NATURAL GAS↗
Development of electroadhesive devices for zero-g intra/extravehicular activities
Chemically activated electroadhesive pads on spacecraft surface, allowing astronauts to maneuver or work in zero gravity environments
Beasley, G. P.↗
A pad perturbation method for the dynamic coefficients of tilting-pad journal bearings
A pad assembly method for analyzing tilting-pad bearings is presented. The method results in the complete coefficient matrix for a tilting-pad bearing; the matrix is independent of the pad inertia, the pitch frequency and the number of degrees of freedom of the pad. A pad assembly method is used because it allows the collection of more bearing data with less computer time than a brute force iterative procedure. The results given show the complete dynamical matrices for a five-pad tilting-pad bearing both including and ignoring the damping effects of the unloaded (top) pads. For a symmetrical tilting-pad bearing the reduced cross-coupling coefficients are zero when the moment of inertia of the pad is ignored.
Allaire, P. E.↗
An optical processor for zero-crossing edge detection
An optical processor for zero-crossing edge detection is presented, which consists of two defocused imaging systems to perform the Gaussian convolutions and a VLSI, ferroelectric liquid crystal spatial light modulator (SLM) to determine the zero-crossings. The zero-crossing SLM is a 32 x 32 array of pixels located on 100 microns centers. Each pixels contains a phototransistor, an auto-scaling amplifier, a zero-crossing detection circuit, and a liquid crystal modulating pad. Electrical and optical characteristics of the zero-crossing SLM are presented along with experimental results of the system.
Jared, David A.↗
Flight investigation of variations in rotorcraft control and display dynamics for hover
Results are presented from a flight test of experimental control/display systems for the U.S. Army/NASA CH-47B variable-stability research helicopter in hovering maneuvers, supplementing the preliminary report of Eshow et al. (1987). The display format was a simplified version of the pilot night-vision system for the Apache AH-64, and the tests measured pilot performance in hover-pad capture and hover-pad tracking tasks (under simulated zero visibility) using displays based on (1) gainlike and (2) integratorlike controlled-element responses to control inputs. The implementation of the vehicle-response dynamics through an explicit model-following control system and the derivation of the display laws are described, and the test results are presented in extensive tables and graphs. Display type (1) was found to be preferred by the pilots and to give generally better performance than type (2).
Eshow, Michelle M.↗
Searching for the QCD Critical Point Along the Pseudo-critical/Freeze-out Line Using Padé-resummed Taylor Expansions of Cumulants of Conserved Charge Fluctuations
Using high-statistics datasets generated in (2+1)-flavor QCD calculations at finite temperature we construct estimators for the radius of convergence from an eighth order series expansion of the pressure as well as the number density. We show that the estimator for pressure and number density will be identical in the asymptotic limit. In the vicinity of the pseudo-critical temperature, T pc ≃ 156.5 MeV, we find the estimator of the radius of convergence to be µ B /T ≳ 3 for strangeness-neutral matter. We also present results for the pole structure of the Pad´e approximants for the pressure at non-zero values of the baryon chemical potential and show that the pole structure of the [4,4] Pad´e is consistent with not having a critical point at temperatures larger than 135 MeV and a baryon chemical potential smaller than µ B /T ~ 2.5.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Development of a large support surface for an air-bearing type zero-gravity simulator
The methods used in producing a large, flat surface to serve as the supporting surface for an air-bearing type zero-gravity simulator using low clearance, thrust-pad type air bearings are described. Major problems encountered in the use of self-leveled epoxy coatings in this surface are discussed and techniques are recommended which proved effective in overcoming these problems. Performance requirements of the zero-gravity simulator vehicle which were pertinent to the specification of the air-bearing support surface are also discussed.
Glover, K. E.↗
Improved Reliability of SiC Pressure Sensors for Long Term High Temperature Applications
We report advancement in the reliability of silicon carbide pressure sensors operating at 600 C for extended periods. The large temporal drifts in zero pressure offset voltage at 600 C observed previously were significantly suppressed to allow improved reliable operation. This improvement was the result of further enhancement of the electrical and mechanical integrity of the bondpad/contact metallization, and the introduction of studded bump bonding on the pad. The stud bump contact promoted strong adhesion between the Au bond pad and the Au die-attach. The changes in the zero offset voltage and bridge resistance over time at temperature were explained by the microstructure and phase changes within the contact metallization, that were analyzed with Auger electron spectroscopy (AES) and field emission scanning electron microscopy (FE-SEM).
Okojie, R. S.↗
Passive zero-gravity leg restraint
A passive zero or microgravity leg restraint is described which includes a central support post with a top and a bottom. Extending from the central support post are a calf pad tab, to which calf pad is attached, and a foot pad tab, to which foot tab is attached. Also extending from central support post are knee pads. When the restraint is in use the user's legs are forced between pads by a user imposed scissors action of the legs. The user's body is then supported in a zero or microgravity neutral body posture by the leg restraint. The calf pad has semi-ridig elastic padding material covering structural stiffener. The foot pad has padding material and a structural stiffener. Knee pads have s structural tube stiffener at their core.
Miller, Christopher R.↗
Fluid-Kinetic Coupling: Advanced Discretizations for Simulations on Emerging Heterogeneous Architectures (LDRD FY20-0643)
Plasma physics simulations are vital for a host of Sandia mission concerns, for fundamental science, and for clean energy in the form of fusion power. Sandia's most mature plasma physics simulation capabilities come in the form of particle-in-cell (PIC) models and magnetohydrodynamics (MHD) models. MHD models for a plasma work well in denser plasma regimes when there is enough material that the plasma approximates a fluid. PIC models, on the other hand, work well in lower-density regimes, in which there is not too much to simulate; error in PIC scales as the square root of the number of particles, making high-accuracy simulations expensive. Real-world applications, however, almost always involve a transition region between the high-density regimes where MHD is appropriate, and the low-density regimes for PIC. In such a transition region, a direct discretization of Vlasov is appropriate. Such discretizations come with their own computational costs, however; the phase-space mesh for Vlasov can involve up to six dimensions (seven if time is included), and to apply appropriate homogeneous boundary conditions in velocity space requires meshing a substantial padding region to ensure that the distribution remains sufficiently close to zero at the velocity boundaries. Moreover, for collisional plasmas, the right-hand side of the Vlasov equation is a collision operator, which is non-local in velocity space, and which may dominate the cost of the Vlasov solver. The present LDRD project endeavors to develop modern, foundational tools for the development of continuum-kinetic Vlasov solvers, using the discontinuous Petrov-Galerkin (DPG) methodology, for discretization of Vlasov, and machine-learning (ML) models to enable efficient evaluation of collision operators. DPG affords several key advantages. First, it has a built-in, robust error indicator, allowing us to adapt the mesh in a very natural way, enabling a coarse velocity-space mesh near the homogeneous boundaries, and a fine mesh where the solution has fine features. Second, it is an inherently high-order, high-intensity method, requiring extra local computations to determine so-called optimal test functions, which makes it particularly suited to modern hardware in which floating-point throughput is increasing at a faster rate than memory bandwidth. Finally, DPG is a residual-minimizing method, which enables high-accuracy computation: in typical cases, the method delivers something very close to the $L^2$ projection of the exact solution. Meanwhile, the ML-based collision model we adopt affords a cost structure that scales as the square root of a standard direct evaluation. Moreover, we design our model to conserve mass, momentum, and energy by construction, and our approach to training is highly flexible, in that it can incorporate not only synthetic data from direct-simulation Monte Carlo (DSMC) codes, but also experimental data. We have developed two DPG formulations for Vlasov-Poisson: a time-marching, backward-Euler discretization and a space-time discretization. We have conducted a number of numerical experiments to verify the approach in a 1D1V setting. In this report, we detail these formulations and experiments. We also summarize some new theoretical results developed as part of this project (published as papers previously): some new analysis of DPG for the convection-reaction problem (of which the Vlasov equation is an instance), a new exponential integrator for DPG, and some numerical exploration of various DPG-based time-marching approaches to the heat equation. As part of this work, we have contributed extensively to the Camellia open-source library; we also describe the new capabilities and their usage. We have also developed a well-documented methodology for single-species collision operators, which we applied to argon and demonstrated with numerical experiments. We summarize those results here, as well as describing at a high level a design extending the methodology to multi-species operators. We have released a new open-source library, MLC, under a BSD license; we include a summary of its capabilities as well.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Full body restraint system
A body restraint system (30) allows the user's body (10) to be in the zero gravity neutral posture. The system (30) includes a waist restraint (32) in the form of a curved, padded unit (34) containing a retractable belt (36) coiled on a spring loaded capstan (38) with a buckle (40) extending from front (42) of the unit (34). A second belt (44) is fastened around the user's waist (16). A clasp (46) is configured to engage the buckle (40). The waist restraint (32) is positioned near foot restraints (52). The foot restraints (52) have foot platforms (59) with pads (60) of a suitable two part attaching material, such as the fasteners available from Minnesota Mining and Manufacturing Company under the trademark Scotchmate Duallock. A mating pad (62) of the material is provided on soles (64) of cotton net shoes (66).
Ryder, Susan↗