SEARCH · Engineering Papers

Results for “source range”

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.

SourceResearch connectionFrom yearThrough year

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

At least 847 records · Page 47

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Multiscale assessment of land surface phenology from harmonized Landsat 8 and Sentinel-2, PlanetScope, and PhenoCam imagery

As the spatial and temporal resolution of remotely sensed imagery has improved over the last four decades, algorithms for monitoring and mapping seasonal changes in surface properties have evolved rapidly. Most recently, the availability of daily PlanetScope imagery has created new opportunities for monitoring the land surface phenology (LSP) of terrestrial ecosystems at high spatial resolution. However, the quality and value of LSP information from PlanetScope imagery have not been systematically examined. In this paper, we evaluate the character and quality of LSP information derived from PlanetScope by comparing time series of vegetation indices and LSP metrics from PlanetScope to corresponding time series and LSP metrics derived from Harmonized Landsat 8 and Sentinel-2 (HLS) imagery and PhenoCams at six sites that span a diverse range of land cover types and climate. Results show that vegetation index time series from all three data sources show high temporal correlation, and LSP metrics derived from HLS, PlanetScope, and PhenoCam show high agreement with negligible bias. Semi-variograms for phenometrics estimated from PlanetScope imagery indicate that the majority of spatial variance captured in PlanetScope phenometrics occurs well below the spatial resolution HLS imagery. At the same time, LSP metrics from HLS are most strongly correlated with the 50–75% quantiles of 3 m LSP metrics from PlanetScope. This indicates that HLS captures the average phenology at sub-pixel scale captured in PlanetScope imagery. Here, our results represent the first comprehensive comparison of LSP metrics estimated from PlanetScope and publicly available moderate spatial resolution imagery, and provide insights regarding: (1) the quality and character of LSP metrics derived from HLS and PlanetScope; and (2) the relative merits and trade-offs associated with the use of each data source for LSP studies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Redox-Induced Structural Reorganization Dictates Kinetics of Cobalt(III) Hydride Formation via Proton-Coupled Electron Transfer

Two-electron, one-proton reactions of a family of [CoCp(dxpe)(NCCH 3 )] 2+ complexes (Cp = cyclopentadienyl, dxpe = 1,2-bis(di(aryl/alkyl)phosphino)ethane) form the corresponding hydride species [HCoCp(dxpe)] + through a stepwise proton-coupled electron transfer process. For three [CoCp(dxpe)(NCCH 3 )] 2+ complexes (dxpe = dppe (1,2-bis(diphenylphosphino)ethane), depe (1,2-bis(diethylphosphino)ethane), and dcpe (1,2-bis(dicyclohexylphosphino)ethane)), peak shift analysis was employed to quantify apparent proton transfer rate constants from cyclic voltammograms recorded with acids ranging 22 pK a units. The apparent proton transfer rate constants correlate with the strength of the proton source for weak acids, but these apparent proton transfer rate constants curiously plateau (k pl ) as the reaction becomes increasingly exergonic. The absolute apparent proton transfer rate constants across both these regions correlate with the steric bulk of the chelating diphosphine ligand, with bulkier ligands leading to slower kinetics (k plateau,depe = 3.5 x 10 7 M -1 s -1 , k plateau,dppe = 1.7 x 10 7 M -1 s -1 , k plateau,dcpe = 7.1 x 10 4 M -1 s -1 ). Mechanistic studies were conducted to identify the cause of the aberrant $k_PT^{app}$–ΔpK a trends. When the deuterated acids are employed, deuterium incorporation in the Cp ring is observed, indicating protonation of the CoCp(dxpe) species to form the corresponding hydride proceeds via initial ligand protonation. Digital simulations of cyclic voltammograms show ligand loss accompanying initial reduction gates subsequent PCET activity at higher driving forces. Together, these experiments reveal the details of the reaction mechanism: reduction of the Co(III) species is followed by dissociation of the bound acetonitrile ligand, subsequent reduction of the unligated Co(II) species to form a Co(I) species is followed by protonation, which occurs at the Cp ring, followed by tautomerization to generate the stable Co(III)-hydride product [HCoCp(dxpe)] + . Analysis as a function of chelating disphosphine ligand, solvent, and acid strength reveals that the ligand dissociation equilibrium is directly influenced by the steric bulk of the phosphine ligands and gates protonation, giving rise to the plateau of apparent proton transfer rate constant with strong acids. The complexity of the reaction mechanism underpinning hydride formation, encompassing dynamic behavior of the entire ligand set, highlights the critical need to understand elementary reaction steps in proton-coupled electron transfer reactions.

14 SOLAR ENERGY↗

DOE OSTI2024

Long-baseline quantum sensor network as dark matter haloscope

Ultralight dark photons constitute a well-motivated candidate for dark matter. A coherent electromagnetic wave is expected to be induced by dark photons when coupled with Standard-Model photons through kinetic mixing mechanism, and should be spatially correlated within the de Broglie wavelength of dark photons. Here we report the first search for correlated dark-photon signals using a long-baseline network of 15 atomic magnetometers, which are situated in two separated meter-scale shield rooms with a distance of about 1700 km. Both the network’s multiple sensors and the shields large size significantly enhance the expected dark-photon electromagnetic signals, and long-baseline measurements confidently reduce many local noise sources. Using this network, we constrain the kinetic mixing coefficient of dark photon dark matter over the mass range 4.1 feV-2.1 peV, which represents the most stringent constraints derived from any terrestrial experiments operating over the aforementioned mass range. Our prospect indicates that future data releases may go beyond the astrophysical constraints from the cosmic microwave background and the plasma heating.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Cross-scale covariance for material property prediction

A simulation can stand its ground against an experiment only if its prediction uncertainty is known. The unknown accuracy of interatomic potentials (IPs) is a major source of prediction uncertainty, severely limiting the use of large-scale classical atomistic simulations in a wide range of scientific and engineering applications. Here we explore covariance between predictions of metal plasticity, from 178 large-scale (~10 8 atoms) molecular dynamics (MD) simulations, and a variety of indicator properties computed at small-scales (≤10 2 atoms). All simulations use the same 178 IPs. In a manner similar to statistical studies in public health, we analyze correlations of strength with indicators, identify the best predictor properties, and build a cross-scale “strength-on-predictors” regression model. This model is then used to estimate regression error over the statistical pool of IPs. Small-scale predictors found to be highly covariant with strength are computed using expensive quantum-accurate calculations and used to predict flow strength, within the statistical error bounds established in our study.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A Representation Fusion Framework for Decoupling Diagnostic Information in Multimodal Learning

Modern medicine increasingly relies on multimodal data, ranging from clinical notes to imaging and genomics, to guide diagnosis and treatment. However, integrating these heterogeneous data sources in a principled and interpretable manner remains a major challenge. We present MODES (Multi-mOdal Disentangled Embedding Space), a representation fusion framework that explicitly separates shared and modality-specific factors of variation, offering a structured latent space for multimodal information that improves both prediction and interpretability. By leveraging pre-trained unimodal foundation models, MODES mitigates the dependency on extensive paired datasets, crucial in data-scarce clinical settings. We introduce a masking strategy that optimizes representation dimensionality by eliminating low-information dimensions, to achieve compact, information-rich representations. Our framework demonstrates superior performance in predicting diagnoses and phenotypes compared to unimodal and conventional fusion models. MODES also enables robust diagnostic inference in missing data scenarios, offering an opportunity toward interpretable and efficient multimodal diagnostics in personalized healthcare.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Insights into the κ/ι-carrageenan metabolism pathway of some marine Pseudoalteromonas species

Pseudoalteromonas is a globally distributed marine-associated genus that can be found in a broad range of aquatic environments, including in association with macroalgal surfaces where they may take advantage of these rich sources of polysaccharides. The metabolic systems that confer the ability to metabolize this abundant form of photosynthetically fixed carbon, however, are not yet fully understood. Through genomics, transcriptomics, microbiology, and specific structure-function studies of pathway components we address the capacity of newly isolated marine pseudoalteromonads to metabolize the red algal galactan carrageenan. The results reveal that the κ/ι-$\underline{car}$rageenan specific $\underline{p}$olysaccharide utilization $\underline{l}$ocus (CarPUL) enables isolates possessing this locus the ability to grow on this substrate. Biochemical and structural analysis of the enzymatic components of the CarPUL promoted the development of a detailed model of the κ/ι-carrageenan metabolic pathway deployed by pseudoalteromonads, thus furthering our understanding of how these microbes have adapted to a unique environmental niche.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Sparse non-Markovian Noise Modeling of Transmon-Based Multi-Qubit Operations

The influence of noise on quantum dynamics is one of the main factors preventing current quantum processors from performing accurate quantum computations. Sufficient noise characterization and modeling can provide key insights into the effect of noise on quantum algorithms and inform the design of targeted error protection protocols. However, constructing effective noise models that are sparse in model parameters, yet predictive can be challenging. In this work, we present an approach for effective noise modeling of multi-qubit operations on transmon-based devices. Through a comprehensive characterization of seven devices offered by the IBM Quantum Platform, we show that the model can capture and predict a wide range of single- and two-qubit behaviors, including non-Markovian effects resulting from spatiotemporally correlated noise sources. The model’s predictive power is further highlighted through multi-qubit dynamical decoupling demonstrations and an implementation of the variational quantum eigensolver. As a training proxy for the hardware, we show that the model can predict expectation values within a relative error of 0.5%; this is a sevenfold improvement over default hardware noise models. Through these demonstrations, we highlight key error sources in superconducting qubits and illustrate the utility of reduced noise models for predicting hardware dynamics.

open quantum systems & decoherence↗

DOE OSTI2020

γ-ray measurements in fast-neutron-induced reactions on 203 Tl

Fast-neutron-induced reactions can be used to characterize reaction mechanisms, investigate nuclear structure, and impose constraints on nuclear models. Because of the difficulty in predicting such effects, experimental data are important to constrain models. Thallium isotopes located close to the doubly magic Pb 208 nucleus are important for comparison with shell-model calculations. Study the population of excited states in Tl 203 and lighter isotopes in such reactions. Our methods are as follows. γ -ray cross sections were measured. The data were taken by using the Germanium Array for Neutron-Induced Excitations spectrometer. The pulsed neutron source of the Los Alamos Neutron Science Center's Weapons Neutron Research facility provided neutrons in the energy range from 1 to 300 MeV. The time-of-flight technique was used to determine the incident neutron energies. Cross sections for emission of several γ rays in 20 reaction channels were determined. Candidates for the intruder 9 / 2 - state in Tl 203 , from the odd proton in the h 9 / 2 orbital, and the first 5 + states in Tl 202 , 204 , from admixture of configurations, were identified. The excitation energy of the candidate 9 / 2 - , π h 9 / 2 state is in good agreement with the theoretical prediction from a semi-empirical weak-coupling model and its half-life is in the range of tens of nanoseconds. The feeding of a previously known isomer in Tl 202 exhibits similarities with the feeding of other isomers in this mass region.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Over 8 hours of continuous operation of a free-electron laser driven by a laser-plasma accelerator

Since the emergence of laser-plasma accelerators (LPAs), substantial work has been dedicated to using LPAs to drive free-electron lasers (FELs) for a broad range of applications. Despite recent breakthroughs, which have proven the fundamental feasibility of operating FELs with an LPA source, stable FEL operation over multiple hours without operator input had yet to be achieved. In this work, we report significant improvements to the stability of a hundred terawatt laser system, resulting in successful demonstration of reliable, long-term operation of an LPA-driven FEL in the self-amplified spontaneous emission (SASE) regime at 420 nm. The LPA source delivered 100 MeV electron beams at 1 Hz with high stability over more than 10 h, enabling over 8 h of continuous FEL operation without operator input. The acquired data were subsequently used to investigate correlations between the measured undulator radiation and parameters of the drive laser, plasma source, and electron beam. The revealed connections between LPA and FEL performance gave important additional insights into ways to further improve and stabilize the system, thus demonstrating the capability of our setup to serve as a powerful platform for future studies of LPA-driven FEL operation. The one-of-a-kind integration of multiple stabilization concepts onto the LPA facility discussed in this manuscript yielded significant accelerator and light source improvements (with residual correlations suggesting even more is possible), which will positively impact LPA applications at large.

Kohrell, Finn [Lawrence Berkeley National Laborato↗

DOE OSTI2024

Machine Learning-Assisted Stability Boundary Determination of Multiport Autonomous Reconfigurable Solar Power Plants

The multiport autonomous reconfigurable solar (MARS) power plant is a promising solution to integrate renewable resources and energy storage systems into the alternating current (ac) power grid and an high-voltage direct current (HVdc) link. In the MARS system, various input power sources are connected to the individual submodules (SMs) through direct current (dc)–dc converters. However, the presence of external power sources can result in unbalanced capacitor voltages of SMs, thereby violating stability constraints under multiple/diverse operating conditions. This article aims to address the gap by accurately determining the stability boundary of the MARS system. As such, a novel machine learning (ML)-assisted energy balancing control (EBC) criterion is proposed. Further, in conjunction with a refined EBC, this approach ensures balanced capacitor voltages across various types of SMs, significantly enhancing the overall system efficiency. The proposed EBC criterion effectively controls EBC activation and deactivation, achieving remarkable accuracy. Both power systems computer aided design (PSCAD)/electromagnetic transients including direct current (EMTDC) simulations and control hardware-in-the-loop (cHIL) tests are conducted to validate the feasibility and efficiency of the proposed method. By combining the EBC and ML-assisted EBC criterion, efficient energy management is achieved for systems featuring multiple input power sources, such as MARS. This approach enables the system to fully exploit its potential across an expanded operational range while upholding high-efficiency standards.

14 SOLAR ENERGY↗

DOE OSTI2020

Prototype design and experimental tests of a zoom mirror system for the APS upgrade

Mirror-based zoom optics systems can offer variable focal spot sizes over a wide range, which is essential for coherent nanoprobe beamlines, such as the proposed Atomic beamline in the Advanced Photon Source (APS) upgrade project. The success of the zoom mirror system in the nano-focusing regime requires the development of high-precision deformable mirrors, in-situ surface profilers and wavefront sensors, and advanced feedback control system. A prototype 1-D zoom mirror system consists of two vertical focusing mirrors was designed, assembled, and tested at the APS 1-BM beamline. The system consists of a bender-based mirror with a capacitive-sensorarray-based real-time mirror profiler, a bimorph adaptive mirror, and a grating interferometer for the wavefront monitoring. In this work, we present the design and test results of the prototype system demonstrating its zoom focusing capability.

adaptive optics↗

DOE OSTI2025

Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE)

Convective clouds play an important role in Earth’s climate system and are a known source of extreme weather. Gaps in our understanding of convective vertical motions, microphysics, and precipitation across a full range of aerosol and meteorological regimes continue to limit our ability to predict the occurrence and intensity of these cloud systems. To improve predictability, the National Science Foundation (NSF) sponsored a large field experiment entitled “Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE).” ESCAPE took place between 30 May and 30 September 2022 in the vicinity of Houston, Texas, because this area frequently experiences isolated deep convection that interacts with the region’s mesoscale circulations and its range of aerosol conditions. ESCAPE focused on collecting observations of isolated deep convection through innovative sampling and developing novel analysis techniques. This included the deployment of two research aircraft, the National Research Council of Canada Convair-580 and the Stratton Park Engineering Company Learjet, which combined conducted 24 research flights from 30 May to 17 June. On the ground, three mobile X-band radars and one mobile Doppler lidar truck equipped with soundings were deployed from 30 May to 28 June. From 1 August to 30 September 2022, a dual-polarization C-band radar was deployed and operated using a novel, multisensor agile adaptive sampling strategy to track the entire life cycle of isolated convective clouds. Analysis of the ESCAPE observations has already yielded preliminary findings on how aerosols and environmental conditions impact the convective life cycle.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Wave-by-Wave Forecasting via Assimilation of Marine Radar Data

Abstract This work describes a phase-resolving wave-forecasting algorithm that is based on the assimilation of marine radar image time series. The algorithm is tested against synthetic data and field observations. The algorithm couples X-band marine radar observations with a phase-resolving wave model that uses the linear mild slope equations for reconstruction of water surface elevations over a large domain of O (km) and a prescribed time window of O (min). The reconstruction also enables wave-by-wave forecasting through forward propagation in space and time. Marine radar image time series provide the input wave observations through a previously given relationship between backscatter intensity and the radial component of the sea surface slope. The algorithm assimilates the wave slope information into the model via a best-fit wave source function at the boundary that minimizes the slope reconstruction error over an annular region at the outer ranges of the radar images. The wave model is then able to propagate the waves across a polar domain to a location of interest at nearer ranges. The constraints on the method for achieving real-time forecasting are identified, and the algorithm is verified against synthetic data and tested using field observations.

Engineering↗

DOE OSTI2022

Flicker: A review of temporal light modulation stimulus, responses, and measures

Flicker has been an important lighting system consideration for over a century. More precise terms are temporal light modulation (TLM) as the stimulus, and responses to TLM as the unwanted visual, cognitive, or physiological consequences. As lighting technology evolved, different forms of TLM emerged, and so did responses to them. Today, some LED systems – encompassing the LED, driver, and control – can result in TLM causing severe unwanted effects, while other LED systems produce no unwanted effects at all. LED systems can deliver a much wider range of luminous waveforms than conventional lighting systems, some exhibiting very high modulation depths. More than any light source before, they can elicit perceptions of the phantom array. Direct flicker effects at modulation frequencies less than about 80 Hz and the stroboscopic effect at frequencies greater than 80 Hz are fairly well understood, but the phantom array effect needs more exploration and characterisation. This review focuses on the technology and research history that led to current metrics for quantifying TLM and human responses to TLM. Notably, visually impaired individuals may exhibit alterations in their response to TLM, but such a discussion is beyond the intent of this review. Thus, the focus is on individuals with normal visual function.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

PRELIMINARY RESULTS OF MAGNETIC AND TEMPERATURE MAP SYSTEM FOR 3 GHz SUPERCONDUCTING RADIO FREQUENCY CAVITIES

Superconducting radio frequency (SRF) cavities are fundamental building blocks of modern particle accelerators. A surface resistance in the tens of nanoOhm range is achieved when cooling these cavities to liquid helium temperature, ~2 - 4 K. One of the leading sources of residual losses in SRF cavities is trapped magnetic flux. Flux trapping mechanism depends on different surface preparations and cool-down conditions. We have designed, developed and commissioned a combined magnetic and temperature mapping system using anisotropic magneto-resistance sensors and carbon resistors, respectively, to study the flux trap mechanism in 3 GHz single-cell niobium cavities. In this contribution, we will describe the experimental apparatus and present preliminary test results.

Parajuli, I. P.↗

DOE OSTI2021

Integrating Cambium Marginal Costs into Electric Sector Decisions: Opportunities to Integrate Cambium Marginal Cost Data into Berkeley Lab Analysis and Technical Assistance

NREL’s Cambium tool generates forward-looking simulations of marginal wholesale electricity costs associated with NREL’s Standard Scenarios. The scenarios include growing shares of variable renewable energy (VRE, i.e. wind and solar), among other power sector assumptions, between 2018 and 2050. The tool’s primary output—hourly costs at more than 130 balancing areas—could serve as public and transparent data source that supports electric-sector decision-making processes across the U.S. Berkeley Lab conducts a large range of analyses that use historical and forward-looking wholesale electricity prices to inform electric-sector decisions. In this report, Berkeley Lab uses its expertise to evaluate the Cambium cost data. We compare Cambium data with historical wholesale prices for the year 2018 and other modeled prices for the year 2030. We then present eight case studies in which Berkeley Lab researchers use Cambium data to replicate previous analyses based on other price datasets. We describe where primary findings and underlying key price dynamics align or differ, and highlight possible novel insights from the Cambium data. Finally, we qualitatively evaluate the suitability of Cambium costs in ten additional Berkeley Lab studies, though a direct comparison with alternative price data was not feasible at this time. The goal is to inform how electric-sector decision-makers and DOE program offices may be able to use this cohesive dataset, and to highlight what improvements to Cambium may make it even more useful.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Opportunities for Renewable Energy, Storage, Vehicle Electrification, and Demand Response in Rajasthan's Power Sector

To support the government of Rajasthan and inform state policy makers, regulators, planners, and system operators on power system trends, NREL undertook a long-term capacity expansion planning study. We used NREL's flagship capacity expansion planning tool for the power sector called the Regional Energy Deployment System India (ReEDS-India) to understand the generation and transmission needs of Rajasthan through 2050. NREL's modeling framework includes co-optimized decisions about generation, energy storage, transmission, and reserves investments needed to meet future demand while maintaining reliable electricity supply. Scenario analysis was conducted to assess a range of potential future scenarios, providing insight for planning agencies, utilities, and local stakeholders about key trends and sources of uncertainty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

PRIMED for the Future: Purposing Raw Intake for Machine Learning-Enabled Detection

The COVID-19 pandemic demonstrated how a novel, elusive, and diffuse biological threat can engender uncertainty and misinformation, and it underscored the need for flexible analytical modalities agnostic to the identity of biological material. Yet even before the pandemic recognition of the limitations of the current, list-based approach, which focuses on known pathogens and biotoxins, and of the importance of agent-agnostic biodetection, was growing within the biosecurity community. In a 2018 report on “Biodefense in the Age of Synthetic Biology,” for example, the National Academy of Sciences stated that “an overreliance on the Select Agent List is a systematic weakness affecting many aspects of the United States’ current biodefense mitigation capability." More recently, a group of biodefense researchers proposed the identification and adoption of “bioagent-agnostic signatures (BASs)” as a way of detecting and characterizing not only existing agents but also novel ones, an approach they believe will “enable a more flexible and resilient biodefense posture." Indeed, the future of biodetection requires us to begin developing novel analytics that can identify anomalies and/or characteristics that indicate a potential threat, whether known or unknown, without looking for a specific signature that has been identified previously. To assess potential threats more rapidly, it is critical to develop agnostic artificial intelligence (AI)/machine learning (ML) systems that can be employed for real-time assessment of the nature and source of a perturbation. Such systems should be multiscale and multi-dimensional, integrating sensor data from a range of biological, chemical, and physical application spaces. Emerging deep learning (DL) models demonstrate exceptional promise for identification of discriminatory features within multi-dimensional datasets. DL models have the capacity to recognize and encode highly complex patterns in a wide range of input data modalities, including images, text, and biological/chemical/physical spectra. As such, they can execute a wide range of assessments and determinations that have traditionally required a human operator.

59 BASIC BIOLOGICAL SCIENCES↗