Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data shift”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Improving the Academic Climate of an R1 STEM Department: Quantified Positive Shifts in Perception

Ongoing efforts to improve diversity in science, technology, engineering, and mathematics (STEM) primarily manifest as attempts to recruit more women and individuals from historically marginalized groups. Yet, these efforts fail to repair the specific, systemic issues within academic communities that hinder diverse individuals from persisting and thriving in STEM. Here, we present the results of a quantitative, multiyear effort to make the academic climate of an R1 STEM department more inclusive. We use a student-led, department-specific, faculty-supported initiative to assess and improve the climate of the Department of Chemistry at the University of California, Berkeley, as a case study. Our results provide quantitative evidence that community discussions grounded in our own data, alongside cooperative community efforts to address the issues present in those data, are effective methods for driving positive change. Longitudinal assessment of our academic climate from 2018 to 2020 via annual department-wide surveys indicates that these interventions have succeeded in shifting the perception of our academic climate. This study confirms the positive outcomes of having a practical, sustainable, and data-driven framework for affecting change within a graduate community.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2001

Effects of Convective Transport of Solute and Impurities on Defect-Causing Kinetics Instabilities

For in-situ studies of the formation and evolution of step patterns during the growth of protein crystals, we have designed and assembled an experimental setup based on Michelson interferometry with the surface of the growing protein crystal as one of the reflective surfaces. The crystallization part of the device allows optical monitoring of a face of a crystal growing at temperature stable within 0.05 C in a developed solution flow of controlled direction and speed. The reference arm of the interferometer contains a liquid-crystal element that allows controlled shifts of the phase of the interferograms. We employ an image processing algorithm which combines five images with a pi/2 phase difference between each pair of images. The images are transferred to a computer by a camera capable of capturing 6-8 frames per second. The device allows data collection data regarding growth over a relatively large area (approximately .3 sq. mm) in-situ and in real time during growth. The estimated dept resolution of the phase shifting interferometry is about 100 A. The lateral resolution, depending on the zoom ratio, varies between 0.3 and 0.6 micrometers. We have now collected quantitative results on the onset, initial stages and development of instabilities in moving step trains on vicinal crystal surfaces at varying supersaturation, position on the facet, crystal size and temperature with the proteins ferritin, apoferritin and thaumatin. Comparisons with theory, especially with the AFM results on the molecular level processes, see below, allow tests of the rational for the effects of convective flows and, as a particular case, the lack thereof, on step bunching.

Vekilov, Peter G.↗
NASA NTRS2002

Effects of Resonance in Quasi-Periodic Oscillators of Neutron Star Binaries

Using a large quantity of Rossi X-Ray Timing Explorer data presented in the literature, I offer a detailed investigation into the accuracy of the quasi-periodic oscillation (QPO) frequency determination. The QPO phenomenon seen in X-ray binaries is possibly a result of the resonance of the intrinsic (eigen) oscillations and harmonic driving forces of the system. I show that the resonances, in the presence of the damping of oscillations, occur at frequencies that are systematically and randomly shifted with respect to the eigenfrequencies of the system. The shift value strongly depends on the damping rate that is measured by the half-width of the QPO feature. Taking into account this effect, I analyze the QPO data for four Z sources, Scorpius X-I, GX 340+0, GX 5-1, and GX 17+2, and two atoll sources, 4U 1728-34 and 4U 0614+09. The transition-layer model (TLM) predicts the existence of the invariant quantity delta, an inclination angle of the magnetospheric axis with respect to the normal to the disk. I calculate delta and the error bars of delta using the resonance shift, and I find that the inferred delta-values are consistent with constants for these four Z sources, in which horizontal-branch oscillation and kilohertz frequencies have been detected and correctly identified. It is shown that the inferred delta are in the range between 5.5 deg and 6.5 deg. I conclude that the TLM seems to be compatible with the data.

Titarchuk, Lev↗
DOE OSTI2022

Hierarchical Conceptual Model Event and Activity Domains for Forecasting State-Sponsored Civil Nuclear Power Activities

In FY20, the Savannah River National Laboratory and the Sanghani Center for Artificial Intelligence and Data Analytics (Virginia Tech) entered a collaboration funded by the Department of Energy’s Office of Defense Nuclear Nonproliferation Research and Development to develop a machine learning based modeling pipeline to extract proliferation events of interest from open data sources. The prototype modeling pipeline that was developed relies on the use of time dependent word embedding models to identify contextual shifts in key words and phrases that act as indicators of events of interest. The FY20- 21 efforts were focused on a narrow topical domain of forecasting “fissile core fabrication” at the Savannah River Site prior to its official announcement in 2018. In FY22, the research team was funded to continue development of the modeling pipeline by applying it to the problem of forecasting new, and/or significant changes to existing, civil nuclear power reactors around the world. In this effort, the development will focus on proving applicability to a broader topical domain and in data environments that may contain more sparse information, relative to the United States. In this report, the worldwide landscape of civil nuclear reactors is outlined, the timeline of interest is defined, and a hierarchical conceptual model is established to identify the activity domains of interest and the event domains of interest. This preliminary effort will guide the curation of a glossary of key terms for data acquisition, as well as the downstream modeling efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Evaluation and development of flow condensation correlations using the data from low GWP refrigerants in an axial micro-fin aluminum tube

To mitigate global warming, the world is transitioning to refrigerants with low global warming potential (GWP). Supporting this shift requires a model that can accurately predict the heat transfer and pressure drop of new refrigerants, crucial for designing efficient heat exchangers. Existing models, however, are largely based on currently deployed refrigerants and primarily developed for unexpanded micro-fin tubes with spiral angles of 6° to 30°. Their applicability to new refrigerants, especially in expanded micro-fin tubes, is uncertain. This study assesses the performance of four well-known condensation models for six emerging refrigerants—R-32, R-454B, R-454C, R-455A, R-1234yf, and R-1234ze(E)—against experimental data. Initially, the Han and Lee (2005) model shows the best prediction accuracy with a mean absolute deviation (MAD) of 22.1 %. To enhance the accuracy of heat transfer models for new refrigerants and geometries with large temperature glides, two approaches are proposed. Here, the first approach applies a simple correction factor, reducing the MAD of the Cavallini et al. (2009) model from 68.2 % to 15.4 %. The second approach uses the variable metric method for minimization, fitting new constants to the data. This optimization results in the Kedzierski and Goncalves (1997) model achieving the highest accuracy, with a MAD of 13.1 %. For pressure drop models, the Cavallini et al. (1997) model is the most accurate with a MAD of 6.4 %, followed by the Haraguchi et al. (1993) model with a MAD of 9.4 %. Due to its simplicity, the Haraguchi et al. (1993) model is a practical option for predicting frictional pressure drop.

Axial micro-fin tubes↗
DOE OSTI2022

Performance of the Initial Implementation of the Shift Monte Carlo Code in SCALE 6.3

The Shift Monte Carlo code will be introduced in SCALE 6.3 as an alternative to the KENO V.a, KENO-VI, and Monaco codes. Calculations were performed to establish the performance of Shift for criticality safety analyses within the criticality safety analyses sequence (CSAS) based on models in the Verified, Archived Library of Inputs and Data (VALID). This test suite contains over 600 critical experiment models covering a broad range of fissile materials and neutron energy spectra. The comparisons presented include calculated k eff values and runtime performance for serial calculations and a selection of parallel calculations. Comparisons are presented for multigroup (MG) and continuous-energy (CE) calculations for KENO V.a and KENO-VI models. Results generated with a beta version of SCALE 6.3 indicate excellent agreement in k eff values between KENO and Shift. The largest differences in the average k eff value calculated for the 15 categories of KENO V.a models are 0.00020 ± 0.00011 Δ k for MG calculations and 0.00011 ± 0.00005 Δ k for CE calculations. Similar comparisons in three categories using KENO-VI result in the largest differences for MG calculations: as 0.00004 ± 0.00003 Δ k , and -0.00002 ± 0.00003 Δ k for CE. The preliminary results also indicate that Shift is faster than KENO on a per particle basis, especially for fast spectrum systems. The uncertainty per history is also higher, however, so the Monte Carlo figure of merit is higher for KENO for thermal and intermediate spectrum systems. As expected, Shift generally has better speedup than KENO for parallel calculations, regardless of neutron energy spectrum.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Object detection with deep learning for rare event search in the GADGET II TPC

In the pursuit of identifying rare two-particle events within the GADGET II Time Projection Chamber (TPC), this paper presents a comprehensive approach for leveraging Convolutional Neural Networks (CNNs) and various data processing methods. To address the inherent complexities of 3D TPC track reconstructions, the data is expressed in 2D projections and 1D quantities. This approach capitalizes on the diverse data modalities of the TPC, allowing for the efficient representation of the distinct features of the 3D events, with no loss in topology uniqueness. Additionally, it leverages the computational efficiency of 2D CNNs and benefits from the extensive availability of pre-trained models. Given the scarcity of real training data for the rare events of interest, simulated events are used to train the models to detect real events. To account for potential distribution shifts when predominantly depending on simulations, significant perturbations are embedded within the simulations. This produces a broad parameter space that works to account for potential physics parameter and detector response variations and uncertainties. These parameter-varied simulations are used to train sensitive 2D CNN object detectors. When combined with 1D histogram peak detection algorithms, this multi-modal detection framework is highly adept at identifying rare, two-particle events in data taken during experiment 21072 at the Facility for Rare Isotope Beams (FRIB), demonstrating a 100% recall for events of interest. Here, we present the methods and outcomes of our investigation and discuss the potential future applications of these techniques.

Convolutional neural network↗
DOE OSTI2024

Contributions From Cloud Morphological Changes to the Interannual Shortwave Cloud Feedback Based on MODIS and ISCCP Satellite Observations

The surface temperature-mediated change in cloud properties, referred to as the cloud feedback, continues to dominate the uncertainty in climate projections. A larger number of contemporary global climate models (GCMs) project a higher degree of warming than the previous generation of GCMs. This greater projected warming has been attributed to a less negative cloud feedback in the Southern Ocean. Here, we apply a novel “double decomposition method” that employs the “cloud radiative kernel” and “cloud regime” concepts, to two data sets of satellite observations to decompose the interannual cloud feedback into contributions arising from changes within and shifts between cloud morphologies. Our results show that contributions from the latter to the cloud feedback are large for certain regimes. We then focus on interpreting how both changes within and between cloud morphologies impact the shortwave cloud optical depth feedback over the Southern Ocean in light of additional observations. Results from the former cloud morphological changes reveal the importance of the wind response to warming increases low- and mid-level cloud optical thickness in the same region. Results from the latter cloud morphological changes reveal that a general shift from thick storm-track clouds to thinner oceanic low-level clouds contributes to a positive feedback over the Southern Ocean that is offset by shifts from thinner broken clouds to thicker mid- and low-level clouds. Our novel analysis can be applied to evaluate GCMs and potentially diagnose shortcomings pertaining to their physical parameterizations of particular cloud morphologies.

58 GEOSCIENCES↗
DOE OSTI2025

Transition Zones at the Changing Coastal Terrestrial‐Aquatic Interface

Coastal soils are a significant but highly uncertain component of global biogeochemical cycles. These systems experience spatial and temporal variability in biogeochemical processes, driven by marsh‐to‐upland gradients and hydrological fluctuations. These fluctuations make it difficult to understand and predict biogeochemical processes in these highly dynamic systems. We studied coastal soil biogeochemistry and its variability (a) at regional scales and (b) across transects from upland forest to marsh, in two contrasting regions—Lake Erie, a freshwater lacustrine system, and Chesapeake Bay, a saltwater estuarine system. Salinity‐related analytes were a key source of variability in soil biogeochemistry, not just in the saltwater system, but surprisingly, also in the freshwater system. We had hypothesized linear trends in biogeochemical parameters along the TAI—however, contrary to expectations, transition soils were not consistently intermediate between upland and marsh endmembers; the non‐monotonic trends of C, P, Fe along our transects suggest that these do not behave as expected and may be difficult to model and predict—thus these are key analytes to study in our regions. Rapidly changing soil factors across coastal gradients (e.g., Ca, K, CEC, and TS) may act as precursors to ecosystem shifts. Our comprehensive soil characterization represents a snapshot of a single timepoint of surface soils and provides essential data for mechanistic modeling of ecosystem dynamics across coastal transects.

Patel, Kaizad F. [Pacific Northwest National Labor↗
DOE OSTI2024

Hydra: Computer Vision for Online Data Quality Monitoring

Hydra is a system utilizing computer vision for near real-time data quality monitoring. Currently operational across all of Jefferson Lab’s experimental halls, it reduces the workload of shift takers by autonomously monitoring diagnostic plots during experiments. Hydra uses "off-the-shelf" supervised learning technologies and is supported by a comprehensive MySQL database. To simplify access, web apps have been developed to facilitate both labeling and monitoring of Hydra’s inferences. Hydra can connect with the alarm system and incorporates complete historical tracking, enabling it to identify issues that shift takers could miss. When issues are detected, a natural first question is: "Why does Hydra think there is a problem?" To answer, Hydra employs Gradient-weighted Class Activation Maps (GradCAM) to identify regions of the image that are important for the specific classification. This interpretive layer enhances transparency and trustworthiness, which is essential for integration with experiment workflows and operation. The Hydra system, results, and sociological considerations for deployment will be discussed.

Jeske, Torri↗
DOE OSTI2022

Ultrafast perturbation of magnetic domains by optical pumping in a ferromagnetic multilayer

Ultrafast optical pumping of spatially nonuniform magnetic textures is known to induce far-from-equilibrium spin transport effects. Here, we use ultrafast x-ray diffraction with unprecedented dynamic range to study the laser-induced dynamics of labyrinth domain networks in ferromagnetic CoFe/Ni multilayers. We detected azimuthally isotropic, odd order, magnetic diffraction rings up to fifth order. The amplitudes of all three diffraction rings quench to different degrees within 1.6 ps. In addition, all three of the detected diffraction rings both broaden by 15% and radially contract by 6% during the quench process. We are able to rigorously quantify a 31% ultrafast broadening of the domain walls via Fourier analysis of the order-dependent quenching of the three detected diffraction rings. Here, the broadening of the diffraction rings is interpreted as a reduction in the domain coherence length, but the shift in the ring radius, while unambiguous in its occurrence, remains unexplained. In particular, we demonstrate that a radial shift explained by domain-wall broadening can be ruled out. With the unprecedented dynamic range of our data, our results provide convincing evidence that labyrinth domain structures are spatially perturbed at ultrafast speeds under far-from-equilibrium conditions, albeit the mechanism inducing the perturbations remains yet to be clarified.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Diaspora: Resilience-Enabling Services for Real-Time Distributed Workflows

The need for real-time processing to enable automated decision making and experimental steering has driven a shift from high-performance computing workflows on a centralized system to a distributed approach that integrates remote data sources, edge devices, and diverse compute facilities. Under this paradigm, data can be processed close to the source where it is generated, thus reducing latency and bandwidth usage. System resilience is thus a key challenge, requiring distributed workflows to survive component failures and to meet stringent quality-of-service requirements, which results in the need to mitigate anomalies such as congestion and low availability of resources. To address these challenges, we propose Diaspora, a unified resilience framework that is inspired by event-driven communication patterns used in public clouds. Specifically, we propose an event fabric that extends across sites, facilities, and computations to provide timely, reliable, and accurate information about data, application, and resource status. On top of the event fabric, we build resilience-enabling services that combine QoS-aware data streaming, resilient data views, resilient compute and data resources, and anomaly detection and prediction, all of which collectively enhance workflow resilience for these scientific cases.

Rao, Nageswara↗
DOE OSTI2024

In-situ FTIR Spectral Deconvolution [SWR-24-60]

In-situ FTIR Spectral Deconvolution contains scripts for the fitting of gaussians to convoluted FTIR spectra. It was specifically developed to handle a time-series of in situ ATR-FTIR spectra, split the spectra into its individual gaussians, and track those peaks as they shift in intensity and energy. Along with the actual fitting script, this repository contains several support scripts for data analysis and recall of prior fit results.

Tremolet de Villers, Bertrand↗
DOE OSTI2023

Enabling AI in synthetic biology through Construction File specification

The Construction File (CF) specification establishes a standardized interface for molecular biology operations, laying a foundation for automation and enhanced efficiency in experiment design. It is implemented across three distinct software projects: PyDNA_CF_Simulator, a Python project featuring a ChatGPT plugin for interactive parsing and simulating experiments; ConstructionFileSimulator, a field-tested Java project that showcases 'Experiment' objects expressed as flat files; and C6-Tools, a JavaScript project integrated with Google Sheets via Apps Script, providing a user-friendly interface for authoring and simulation of CF. The CF specification not only standardizes and modularizes molecular biology operations but also promotes collaboration, automation, and reuse, significantly reducing potential errors. The potential integration of CF with artificial intelligence, particularly GPT-4, suggests innovative automation strategies for synthetic biology. While challenges such as token limits, data storage, and biosecurity remain, proposed solutions promise a way forward in harnessing AI for experiment design. This shift from human-driven design to AI-assisted workflows, steered by high-level objectives, charts a potential future path in synthetic biology, envisioning an environment where complexities are managed more effectively.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

First Cosmology Results using Supernovae Ia from the Dark Energy Survey: Survey Overview, Performance, and Supernova Spectroscopy

We present details on the observing strategy, data-processing techniques, and spectroscopic targeting algorithms for the first three years of operation for the Dark Energy Survey Supernova Program (DES-SN). This five-year program using the Dark Energy Camera mounted on the 4 m Blanco telescope in Chile was designed to discover and follow supernovae (SNe) Ia over a wide redshift range (0.05 < z < 1.2) to measure the equation-of-state parameter of dark energy. We describe the SN program in full: strategy, observations, data reduction, spectroscopic follow-up observations, and classification. From three seasons of data, we have discovered 12,015 likely SNe, 308 of which have been spectroscopically confirmed, including 251 SNe Ia over a redshift range of 0.017 < z < 0.85. We determine the effective spectroscopic selection function for our sample and use it to investigate the redshift-dependent bias on the distance moduli of SNe Ia we have classified. The data presented here are used for the first cosmology analysis by DES-SN (“DES-SN3YR”), the results of which are given in Dark Energy Survey Collaboration et al. The 489 spectra that are used to define the DES-SN3YR sample are publicly available at https://des.ncsa.illinois.edu/releases/sn.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1976

Experimental investigation of a double-diffused MOS structure

Self-aligned polysilicon gate technology was applied to double-diffused MOS (DMOS) construction in a manner that retains processing simplicity and effectively eliminates parasitic overlap capacitance because of the self-aligning feature. Depletion mode load devices with the same dimensions as the DMOS transistors were integrated. The ratioless feature results in smaller dimension load devices, allowing for higher density integration with no increase in the processing complexity of standard MOS technology. A number of inverters connected as ring oscillators were used as a vehicle to test the performance and to verify the anticipated benefits. The propagation time-power dissipation product and process related parameters were measured and evaluated. This report includes (1) details of the process; (2) test data and design details for the DMOS transistor, the load device, the inverter, the ring oscillator, and a shift register with a novel tapered geometry for the output stages; and (3) an analytical treatment of the effect of the distributed silicon gate resistance and capacitance on the speed of DMOS transistors.

Lin, H. C.↗
NASA NTRS1977

A CW ultrasonic bolt-strain monitor

There exists a need for a relatively inexpensive system for measuring strain in bolts. The torque wrench is one technique for straining bolts which has been widely applied. Unfortunately, friction in the bolt threads and between the nut and the work tend to make such a simple system inaccurate. In practice, a torque wrench is unacceptable for many situations where strain is critical. In this article, an ultrasonic technique is described which can indicate changes in bolt strain to better than one part in 10,000. The technique is based on the one-dimensional propagating-ultrasonic-wave model and uses a new ultrasonic instrument called a Reflection Oscillator Ultrasonic Spectrometer which is a closed-loop feedback marginal-oscillator system that frequency locks the device to the peak of a mechanical resonance in the bolt. The instrument indicates a shift in the bolt resonance frequency due to elongation and changes in velocity of sound due to strain. Data are presented comparing a standard torque wrench to the ultrasonic monitor for different measured stresses on the bolt as well as for different bolt conditions. The strain instrument can be used to monitor changing stresses, to measure material properties and may be applied as a strain gage or load cell.

Heyman, J. S.↗
NASA NTRS1980

A determination of the orbit of GX 301-2

The pulse phase of GX 301-2(4U 1223-62) was tracked for 30 days with the SAS 3 satellite during 1979 January and February. It is suggested that most of the observed changes in pulse period are the result of Doppler shifts in a binary orbit, as opposed to changes in the intrinsic pulse period alone. The SAS 3 data allow orbital periods P(orb) equal to or greater than 23 days when a constant rate of change in the intrinsic pulse period is allowed as a free parameter in the orbital fits. For each trial orbital period the other orbital elements of the binary system are well determined. The SAS 3 data is combined with the Ariel 5 pulse arrival-time data to further restrict the allowed orbits. In both data sets a sharp minimum is observed in the Doppler delays of the pulse arrival times. Evidence is presented that the correct orbit is most likely the one with P(orb) = 35.0d, a projected semimajor axis for the neutron star of 304 light-seconds, and an eccentricity of 0.44. The relation of this system to the six X-ray binaries whose orbits have been determined previously is also discussed.

Kelley, R.↗