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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Travelling wave‐based fault detection and location in a real low‐voltage DC microgrid

Abstract This paper discusses a device‐level implementation of a travelling wave (TW) protection device (PD) designed for a real low‐voltage DC microgrid. The TWPD fault detection and location algorithm is executed on a commercial digital signal processor (DSP) board, involving signal sampling at 1 MHz via the DSP board's analog‐to‐digital converter (ADC). The analogue input card measures positive pole, negative pole and pole‐to‐pole voltages at the TWPD location. Upon a successful fault detection using a second‐order high‐pass filter, the voltage data is normalised and multi‐resolution analysis (MRA) is performed on a 128‐sample buffer around the TW arrival time. MRA employs the discrete wavelet transform (DWT) to capture high‐frequency voltage patterns, and then the Parseval's energy theorem quantifies these TW characteristics by computing the energy of reconstructed wavelet coefficients. These energy values per decomposed frequency band are the basis for training a random forest classifier that predicts fault location and type. The TWPD is fully implemented and connected to a real DC microgrid in Albuquerque, NM, USA, for validation, and results are shown for field tests verifying the performance under faults.

Paruthiyil, Sajay Krishnan [Department of Electric↗
DOE OSTI2026

Spatiotemporal Learning in Power Modules: Wavelet-Enhanced Forecasting of Thermomechanical Degradation

Detecting internal defects in power electronics packages is critical for their performance and reliability, especially under extreme operating conditions, as these defects can lead to catastrophic failure if not properly addressed. Confocal scanning acoustic microscopy (C-SAM) plays a key role in the nondestructive evaluation of bond layer degradation within a power electronics package by detecting defects such as delamination, voids, and cracks. However, accurately quantifying and predicting these defects from C-SAM images remains a significant challenge due to the low noise-to-signal ratio, which typically arises from both imaging process and bond patterns itself. In this paper, we explore machine learning strategies for processing C-SAM images and providing predictive models of defect growth. We use C-SAM images of sintered copper and sintered silver samples, which are obtained under accelerated thermal experiments, as the representative dataset for our study. We investigate the effect of Fourier transforms and wavelet transforms on these datasets to remove high-frequency noise and address noise across multiple scales with histogram equalization to enhance the contrast and improve the visibility of defects. As a result, defect boundaries can be clearly distinguished, enabling more accurate tracking of their growth over time. We then employ different time-series forecasting algorithms on the denoised images to formulate an image-based lifetime prediction model. Statistical models and deep-learning techniques are trained on images obtained in the early stages of thermal shock, and defect growth in the later stages is predicted. Our work serves as a preliminary attempt to improve the accuracy of lifetime prediction models of power electronics packages, which is critical under extreme operating environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Production Application Performance Data Streaming for System Monitoring

In this article, we present an approach to streaming collection of application performance data. Practical application performance tuning and troubleshooting in production high-performance computing (HPC) environments requires an understanding of how applications interact with the platform, including (but not limited to) parallel programming libraries such as Message Passing Interface (MPI). Several profiling and tracing tools exist that collect heavy runtime data traces either in memory (released only at application exit) or on a file system (imposing an I/O load that may interfere with the performance being measured). Although these approaches are beneficial in development stages and post-run analysis, a systemwide and low-overhead method is required to monitor deployed applications continuously. This method must be able to collect information at both the application and system levels to yield a complete performance picture. In our approach, an application profiler collects application event counters. A sampler uses an efficient inter-process communication method to periodically extract the application counters and stream them into an infrastructure for performance data collection. We implement a tool-set based on our approach and integrate it with the Lightweight Distributed Metric Service (LDMS) system, a monitoring system used on large-scale computational platforms. LDMS provides the infrastructure to create and gather streams of performance data in a low overhead manner. We demonstrate our approach using applications implemented with MPI, as it is one of the most common standards for the development of large-scale scientific applications. We utilize our tool-set to study the impact of our approach on an open source HPC application, Nalu. Our tool-set enables us to efficiently identify patterns in the behavior of the application without source-level knowledge. We leverage LDMS to collect system-level performance data and explore the correlation between the system and application events. Finally, we demonstrate how our tool-set can help detect anomalies with a low latency. We run tests on two different architectures: a system enabled with Intel Xeon Phi and another system equipped with Intel Xeon processor. Our overhead study shows our method imposes at most 0.5% CPU usage overhead on the application in realistic deployment scenarios.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Spatially Resolved Velocity Structures in Jets of DF Tau and UY Aur A

Young stars accrete mass and angular momentum from their circumstellar disks. Some of them also drive outflows, which can be distinguished in optical forbidden emission lines. We analyze a sample of binary T Tauri stars observed with long-slit spectroscopy by the Hubble Space Telescope between 1998 and 2000, searching for spatially resolved outflows. We detect resolved [O i] emission in 2 cases out of 21. In DF Tau we resolve high- and medium-velocity outflows in a jet and counterjet out to 60 au. The outflows are accelerated within the inner 12 au and retain a constant speed thereafter. In UY Aur, we detect a blue- and a redshifted outflow from UY Aur A, as well as a blueshifted jet from UY Aur B. All of these features have been seen in [Fe ii] with data taken 10 years apart indicating that the underlying outflow pattern is stable on these timescales.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Constraining Mornings and Evenings on Distant Worlds: A new Semianalytical Approach and Prospects with Transmission Spectroscopy

The technique of transmission spectroscopy—the variation of a planetary radius with wavelength due to opacity sources in the planet’s terminator region—has been one of the most successful in the characterization of exoplanet atmospheres to date, providing key insights into the composition and structure of these distant worlds. A common assumption made when using this technique, however, is that the variations are the same in the entire terminator region. In reality, the morning and evening terminators might have distinct temperature, pressure, and thus compositional profiles due to the inherent 3D nature of the planet, which would, in turn, give rise to different spectra on each side of it. Constraining those might be fundamental for our understanding of not only the weather patterns in these distant worlds but also the planetary formation signatures that might only be possible to extract once these features are well understood. Motivated by this physical picture, in this work, we perform a detailed study of the observational prospects of detecting this effect. We present an open-source semianalytical framework with which this information can be extracted directly from transit light curves and perform a detailed study of the prospects of detecting the effect with current missions, such as TESS, and upcoming ones, such as JWST. Our results show that these missions show great promise for the detection of this effect. Transmission spectroscopy studies with JWST, in particular, could provide spectra of each of the limbs, allowing us to convey 3D information previously accessible only via phase curves.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Effects of antenna beam chromaticity on redshifted 21 cm power spectrum and implications for hydrogen epoch of reionization array

Unaccounted for systematics from foregrounds and instruments can severely limit the sensitivity of current experiments from detecting redshifted 21 cm signals from the Epoch of Reionization (EoR). Upcoming experiments are faced with a challenge to deliver more collecting area per antenna element without degrading the data with systematics. This paper and its companions show that dishes are viable for achieving this balance using the Hydrogen Epoch of Reionization Array (HERA) as an example. Here, we specifically identify spectral systematics associated with the antenna power pattern as a significant detriment to all EoR experiments which causes the already bright foreground power to leak well beyond ideal limits and contaminate the otherwise clean EoR signal modes. A primary source of this chromaticity is reflections in the antenna-feed assembly and between structures in neighboring antennas. Using precise foreground simulations taking wide-field effects into account, we provide a generic framework to set cosmologically motivated design specifications on these reflections to prevent further EoR signal degradation. We show that HERA will not be impeded by such spectral systematics and demonstrate that even in a conservative scenario that does not perform removal of foregrounds, HERA will detect the EoR signal in line-of-sight k-modes, k{sub ∥}≳0.2 h Mpc{sup −1}, with high significance. Under these conditions, all baselines in a 19-element HERA layout are capable of detecting EoR over a substantial observing window on the sky.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Respiration Signal Pattern Analysis for Doppler Radar Sensor with Passive Node and Its Application in Occupancy Sensing of a Stationary Subject

Doppler radar node occupancy sensors are promising for applications in smart buildings due to their simple circuits and price advantage compared to quadrature radar sensors. However, single-channel sensitivity limitations may result in low sensitivity and misinterpreted motion rates if the detected subject is at or close to “null” points. We designed and tested a novel method to eliminate such limits, demonstrating that passive nodes can be used to detect a sedentary person regardless of position. This method is based on characteristics of chest motion due to respiration, found via both simulations and experiments based on a sinusoidal model and a more realistic model of cardiorespiratory motion. In addition, respiratory rate variability is considered to distinguish a true human presence from a mechanical target. Sensor node data were collected simultaneously with an infrared camera system, which provided a respiration signal reference, to test the algorithm with 19 human subjects and a mechanical target. The results indicate that a human presence was detected with 100% accuracy and successfully differentiated from a mechanical target in a controlled environment. The developed method can greatly improve the occupancy detection accuracy of single-channel radar-based occupancy sensors and facilitate their adoption in smart building applications.

Song, Chenyan↗
DOE OSTI2023

Scalable Incremental Checkpointing using GPU-Accelerated De-Duplication

Writing large amounts of data concurrently to stable storage is a typical I/O pattern of many HPC workflows. This pattern introduces high I/O overheads and results in increased storage space utilization especially for workflows that need to capture the evolution of data structures with high frequency as checkpoints. In this context, many applications, such as graph pattern matching, perform sparse updates to large data structures between checkpoints. For these applications, incremental checkpointing techniques that save only the differences from one checkpoint to another can dramatically reduce the checkpoint sizes, I/O bottlenecks, and storage space utilization. However, such techniques are not without challenges: it is non-trivial to transparently determine what data has changed since a previous checkpoint and assemble the differences in a compact fashion that does not result in excessive metadata. State-of-art data reduction techniques (e.g., compression and de-duplication) have significant limitations when applied to modern HPC applications that leverage GPUs: slow at detecting the differences, generate a large amount of metadata to keep track of the differences, and ignore crucial spatiotemporal checkpoint data redundancy. This paper addresses these challenges by proposing a Merkle tree-based incremental checkpointing method to exploit GPUs' high memory bandwidth and massive parallelism. Experimental results at scale show a significant reduction of the I/O overhead and space utilization of checkpointing compared with state-of-the-art incremental checkpointing and compression techniques.

Tan, Nigel↗
DOE OSTI2015

An optimization of the FPGA trigger based on the artificial neural network for a detection of neutrino-origin showers

Observations of ultra-high energy neutrinos became a priority in experimental astro-particle physics. Up to now, the Pierre Auger Observatory did not find any candidate on a neutrino event. This imposes competitive limits to the diffuse flux of ultra-high energy neutrinos in the EeV range and above. A very low rate of events potentially generated by neutrinos is a significant challenge for a detection technique and requires both sophisticated algorithms and high-resolution hardware. A trigger based on a artificial neural network was implemented into the Cyclone{sup R} V E FPGA 5CEFA9F31I7. The prototype Front-End boards for Auger-Beyond-2015 with Cyclone{sup R} V E can test the neural network algorithm in real pampas conditions in 2015. Showers for muon and tau neutrino initiating particles on various altitudes, angles and energies were simulated in CORSICA and Offline platforms giving pattern of ADC traces in Auger water Cherenkov detectors. The 3-layer 12-10-1 neural network was taught in MATLAB by simulated ADC traces according the Levenberg-Marquardt algorithm. Results show that a probability of a ADC traces generation is very low due to a small neutrino cross-section. Nevertheless, ADC traces, if occur, for 1-10 EeV showers are relatively short and can be analyzed by 16-point input algorithm. For 100 EeV range traces are much longer, but with significantly higher amplitudes, which can be detected by standard threshold algorithms. We optimized the coefficients from MATLAB to get a maximal range of potentially registered events and for fixed-point FPGA processing to minimize calculation errors. Currently used Front-End boards based on no-more produced ACEXR PLDs and obsolete Cyclone{sup R} FPGAs allow an implementation of relatively simple threshold algorithms for triggers. New sophisticated trigger implemented in Cyclone{sup R} V E FPGAs with large amount of DSP blocks, embedded memory running with 120 - 160 MHz sampling may support to discover neutrino events in the Pierre Auger Observatory. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Power grid frequency prediction using spatiotemporal modeling

Understanding power system dynamics is essential for interarea oscillation analysis and the detection of grid instabilities. The FNET/GridEye is a GPS-synchronized wide-area frequency measurement network that provides an accurate picture of the normal real-time operational condition of the power system-dynamics, giving rise to new and intricate spatiotemporal patterns of power loads. We propose to model FNET/GridEye grid frequency data from the U.S. Eastern Interconnection with a spatiotemporal statistical model. We predict the frequency data at locations without observations, a critical need during disruption events where measurement data are inaccessible. Spatial information is accounted for either as neighboring measurements in the form of covariates or with a spatiotemporal correlation model captured by a latent Gaussian field. Finally, the proposed method is useful in estimating power system dynamic response from limited phasor measurements and holds promise for predicting instability that may lead to undesirable effects such as cascading outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Combining Mass Spectrometry of Picoliter Samples with a Multicompartment Electrodynamic Trap for Probing the Chemistry of Droplet Arrays

Single droplet levitation provides contactless access to the microphysical and chemical properties of micrometer-sized samples. Most applications of droplet levitation to chemical and biological systems use nondestructive optical techniques to probe droplet properties. To provide improved chemical specificity, we coupled a multicompartment quadrupole electrodynamic trap (QET) with single droplet mass spectrometry. Our QET continuously traps a monodisperse droplet population (tens to hundreds of droplets) and allows for the simultaneous sizing of a single droplet using its Mie scattering pattern. Single droplets are subsequently ejected into the ionization region of an ambient pressure inlet mass spectrometer. We optimized two complementary soft ionization techniques for picoliter aqueous droplets: (1) paper spray (PS) ionization and (2) thermal desorption glow discharge (TDGD) ionization. Both techniques detect oxygenated organic acids in single droplets, with signal-to-noise ratios >100 and detection limits on the order of 10 pg. Sensitivity and reproducibility across single droplets are driven by the droplet deposition location and spray stability in PS-MS and the ionization region humidity and analyte evaporation rate in TDGD-MS. Importantly, the analyte evaporation rate can control the TDGD-MS quantitative capability because high evaporation rates result in significant ion suppression. Additionally, this effect is mitigated by optimizing the vaporization temperature, droplet size range, and analyte volatility. We demonstrate quantitative and reproducible measurements with a droplet internal standard (<10% RSD) and compare the sensitivity of PS-MS and TDGD-MS. Finally, we demonstrate the application of QET-MS to the study of heterogeneous chemical kinetics with the reaction of gas phase O 3 and aqueous maleic acid droplets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Synergistic Removal of Zinc and Copper in Greenhouse Waste Effluent by Struvite

Struvite (MgNH 4 PO 4 ·6H 2 O) can be recovered from wastewaters for mitigation of phosphorus content. However, the interaction of dissolved constituents with struvite is rarely evaluated. Removal of heavy metals and total organic carbon (TOC) in a greenhouse wastewater (GW) by struvite was investigated in this work. Presynthesized struvite was added to GW and removal of Zn (689 μg/L), Cu (151 μg/L), and TOC (51 mg/L) monitored from 1 to 26 d. Metal uptake in sodium nitrate solutions was used to assess competition, and the influence of other GW constituents on sorption. Struvite was also directly precipitated from GW (PPT). Recovered GW solids had 64–247 mg/kg Zn, 12–54 mg/kg Cu, and 1721–8806 mg/kg TOC, with lowest loadings for PPT and highest for 26 d solids. X-ray absorption spectroscopy detected polymerized Zn-phosphate, induced by dissolved phosphorus in GW, and Cu copolymerization, initially limited by aqueous Cu-organic complexation. Sorbed Cu shifts Fourier transform infrared-sensitive phosphate bands and changes the intensities of reflections in X-ray diffraction patterns of struvite more so than Zn. Struvite from GW is more susceptible to thermal decomposition than unreacted struvite, evolving CO(g), CO 2 (g), NH 3 (g), and H 2 O(g). Therefore, struvite from GW sorbs metals and organics, and can release sorbed and structural components to the aqueous and gas phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

All-in-all-out magnetic domain size in pyrochlore iridate thin films as probed by local magnetotransport

Pyrochlore iridates have attracted growing attention because of a theoretical prediction of a possible topological semimetal phase originating from all-in-all-out spin ordering. Related to the topological band structure, recent findings of the magnetic domain wall conduction have stimulated investigations of magnetic domain distribution in this system. Here, we investigate the size of magnetic domains in Eu{sub 2}Ir{sub 2}O{sub 7} single crystalline thin films by magnetoresistance (MR) using microscale Hall bars. Two distinct magnetic domains of the all-in-all-out spin structure are known to exhibit linear MR but with opposite signs, which enables us to estimate the ratio of the two domains in the patterned channel. The linear MR for 80 × 60 μm{sup 2} channel is nearly zero after zero-field cooling, suggesting random distribution of domains smaller than the channel size. In contrast, the wide distribution of the value of the linear MR is detected in 2 × 2 μm{sup 2} channel, reflecting the detectable domain size depending on each cooling-cycle. Compared to simulation results, we estimate the average size of a single all-in-all-out magnetic domain as 1–2 μm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Development of a wide bandwidth heterodyne dispersion interferometer for electron density measurement of atmospheric pressure plasmas

One of the challenges of electron density measurements of an atmospheric pressure plasma (APP) with a laser interferometer is the significant and unwanted phase shift caused by changes in the neutral gas density. These unwanted phase shifts can be mitigated and plasma density measured using an interferometer architecture called a dispersion interferometer (DI). A DI is composed of two nonlinear orientation patterned GaAs crystals for frequency doubling and measures the phase shift induced by a plasma in the interference signal between two second-harmonic beams. Measurement of plasma dynamics or a short plasma pulse in less than a millisecond is enabled with heterodyne detection in a DI using an acousto-optic cell with a frequency of 40 MHz. This heterodyne DI (HDI) is targeted to measure APPs in an electron density range of 10 20 –10 24 m −3 . Finally, the HDI achieves a line-integrated density resolution of 2 × 10 15 m −2 (a phase resolution of 0.005°) with a time constant of 1 μs using ensemble averaging techniques.

atmospheric pressure plasma↗
DOE OSTI2016

Science with the space-based interferometer LISA. IV: probing inflation with gravitational waves

We investigate the potential for the LISA space-based interferometer to detect the stochastic gravitational wave background produced from different mechanisms during inflation. Focusing on well-motivated scenarios, we study the resulting contributions from particle production during inflation, inflationary spectator fields with varying speed of sound, effective field theories of inflation with specific patterns of symmetry breaking and models leading to the formation of primordial black holes. The projected sensitivities of LISA are used in a model-independent way for various detector designs and configurations. We demonstrate that LISA is able to probe these well-motivated inflationary scenarios beyond the irreducible vacuum tensor modes expected from any inflationary background.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

SU-F-T-549: Validation of a Method for in Vivo 3D Dose Reconstruction for SBRT Using a New Transmission Detector

Purpose: Recently, there has been increased clinical use of stereotactic body radiation therapy (SBRT). SBRT treatments will strongly benefit from in vivo patient dose verification, as any errors in delivery can be more detrimental to the radiobiology of the patient as compared to conventional therapy. In vivo dose measurements, a commercially available quality assurance platform which is able to correlate the delivered dose to the patient’s anatomy and take into account tissue inhomogeneity, is the COMPASS system (IBA Dosimetry, Germany) using a new transmission detector (Dolphin, IBA Dosimetry). In this work, we evaluate a method for in vivo 3D dose reconstruction for SBRT using a new transmission detector, which was developed for in vivo dose verification for intensity-modulated radiation therapy (IMRT). Methods: We evaluated the accuracy of measurement for SBRT using simple small fields (2×2−10×10 cm2), a multileaf collimator (MLC) test pattern, and clinical cases. The dose distributions from the COMPASS were compared with those of EDR2 films (Kodak, USA) and the Monte Carlo simulations (MC). For clinical cases, we compared MC using dose-volume-histograms (DVHs) and dose profiles. Results: The dose profiles from the COMPASS for small fields and the complicated MLC test pattern agreed with those of EDR2 films, and MC within 3%. This showed the COMPASS with Dolphin system showed good spatial resolution and can measure small fields which are required for SBRT. Those results also suggest that COMPASS with Dolphin is able to detect MLC leaf position errors for SBRT. In clinical cases, the COMPASS with Dolphin agreed well with MC. The Dolphin detector, which consists of ionization chambers, provided stable measurement. Conclusion: COMPASS with Dolphin detector showed a useful in vivo 3D dose reconstruction for SBRT. The accuracy of the results indicates that this approach is suitable for clinical implementation.

60 APPLIED LIFE SCIENCES↗