SEARCH · Engineering Papers

Results for “Differentiability”

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 1,063 records · Page 59

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Predicting the Slowing of Stellar Differential Rotation by Instability-driven Turbulence

Abstract Differentially rotating stars and planets transport angular momentum (AM) internally due to turbulence at rates that have long been a challenge to predict reliably. We develop a self-consistent saturation theory, using a statistical closure approximation, for hydrodynamic turbulence driven by the axisymmetric Goldreich–Schubert–Fricke instability at the stellar equator with radial differential rotation. This instability arises when fast thermal diffusion eliminates the stabilizing effects of buoyancy forces in a system where a stabilizing entropy gradient dominates over the destabilizing AM gradient. Our turbulence closure invokes a dominant three-wave coupling between pairs of linearly unstable eigenmodes and a near-zero frequency, viscously damped eigenmode that features latitudinal jets. We derive turbulent transport rates of momentum and heat and provide them in analytic forms. Such formulae, free of tunable model parameters, are tested against direct numerical simulations; the comparison shows good agreement. They improve upon prior quasi-linear or “parasitic saturation” models containing a free parameter. Given model correspondences, we also extend this theory to heat and compositional transport for axisymmetric thermohaline-instability-driven turbulence in certain regimes.

Astronomy & Astrophysics↗

DOE OSTI2025

Joint Modeling of Quasar Variability and Accretion Disk Reprocessing Using Latent Stochastic Differential Equations

Quasars are bright active galactic nuclei powered by the accretion of matter around supermassive black holes at the center of galaxies. Their stochastic brightness variability depends on the physical properties of the accretion disk and black hole. The upcoming Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to observe tens of millions of quasars, so there is a need for efficient techniques like machine learning that can handle the large volume of data. Quasar variability is believed to be driven by an X-ray corona, which is reprocessed by the accretion disk and emitted as UV/optical variability. We are the first to introduce an auto-differentiable simulation of the accretion disk and reprocessing. We use the simulation as a direct component of our neural network to jointly model the driving variability and reprocessing, trained with supervised learning on simulated LSST-like 10 yr quasar light curves. We encode the light curves using a transformer encoder, and the driving variability is reconstructed using latent stochastic differential equations, a physically motivated generative deep learning method that can model continuous-time stochastic dynamics. By embedding the physical processes of the driving signal and reprocessing into our network, we achieve a model that is more robust and interpretable. We demonstrate that our model outperforms a Gaussian process regression baseline and can infer accretion disk parameters and time delays between wave bands, even for out-of-distribution driving signals. Our approach provides a powerful framework that can be adapted to solve other inverse problems in multivariate time series.

Fagin, Joshua [City Univ. of New York (CUNY), NY (↗

DOE OSTI2021

Data from: Niche differentiation of bacterial versus archaeal soil nitrifiers induced by ammonium inhibition along a management gradient

Soil nitrification, mediated mainly by ammonia oxidizing archaea (AOA) and bacteria (AOB), converts ammonium (NH4+) to nitrite (NO2−) and thence nitrate (NO3−). To better understand ecological differences between AOA and AOB, we investigated the nitrification kinetics of AOA and AOB under eight replicated cropped and unmanaged ecosystems (including two fertilized natural systems) along a long-term management intensity gradient in the upper U.S. Midwest. For five of eight ecosystems, AOB but not AOA exhibited Haldane kinetics (inhibited by high NH4+ additions), especially in perennial and successional systems. In contrast, AOA predominantly exhibited Michaelis-Menten kinetics, suggesting greater resistance to high nitrogen inputs than AOB. These responses suggest the potential for NH4+-induced niche differentiation between AOA and AOB. Additionally, long-term fertilization significantly enhanced maximum nitrification rates (Vmax) in the early successional systems for both AOA and AOB, but not in the deciduous forest systems. This was likely due to pH suppression of nitrification in the acidic forest soils, corroborated by a positive correlation of Vmax with soil pH but not with amoA gene abundance. Results also demonstrated that soil nitrification potentials were relatively stable, as there were no seasonal differences. Overall, results suggest that (1) NH4+ inhibition of AOB but not AOA could be another factor contributing to niche differentiation between AOA and AOB in soil, and (2) nitrification by both AOA and AOB can be significantly promoted by long-term nitrogen inputs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Efficacy of a portable, moderate-resolution, fast-scanning differential mobility analyzer for ambient aerosol size distribution measurements

Abstract. Ambient aerosol size distributions obtained with a compact scanning mobility analyzer, the “Spider” differential mobility analyzer (DMA), are compared to those obtained with a conventional mobility analyzer, with specific attention to the effect of mobility resolution on the measured size distribution parameters. The Spider is a 12 cm diameter radial differential mobility analyzer that spans the 10–500 nm size range with 30 s mobility scans. It achieves its compact size by operating at a nominal mobility resolution R=3 (sheath flow = 0.9 L min−1; aerosol flow = 0.3 L min−1) in place of the higher ratio of sheath flow to aerosol flow commonly used. The question addressed here is whether the lower resolution is sufficient to capture key characteristics of ambient aerosol size distributions. The Spider, operated at R=3 with 30 s up- and downscans, was co-located with a TSI 3081 long-column mobility analyzer, operated at R=10 with a 360 s sampling duty cycle. Ambient aerosol data were collected over 26 consecutive days of continuous operation, in Pasadena, CA. Over the 17–500 nm size range, the two instruments exhibit excellent correlation in the total particle number concentrations and geometric mean diameters, with regression slopes of 1.13 and 1.00, respectively. Our results suggest that particle sizing at a lower resolution than typically employed may be sufficient to obtain key properties of ambient size distributions, at least for these two moments of the size distribution. Moreover, it enables better counting statistics, as the wider transfer function for a given aerosol flow rate results in a higher counting rate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Extending water vapor measurement capability of photon-limited differential absorption lidars through simultaneous denoising and inversion

Abstract. The micropulse differential absorption lidar (MPD) was developed at Montana State University (MSU) and the National Center for Atmospheric Research (NCAR) to perform range-resolved water vapor (WV) measurements using low-power lasers and photon-counting detectors. The MPD has proven to produce accurate WV measurements up to 6 km altitude. However, the MPD's ability to produce accurate higher-altitude WV measurements is impeded by the current standard differential absorption lidar (DIAL) retrieval methods. These methods are built upon a fundamental methodology that algebraically solves for the WV using the MPD forward models and noisy observations, which exacerbates any random noise in the lidar observations. The work in this paper introduces the adapted Poisson total variation (PTV) specifically for the MPD instrument. PTV was originally developed for a ground-based high spectral resolution lidar, and this paper reports on the adaptations that were required in order to apply PTV on MPD WV observations. The adapted PTV method, coined PTV-MPD, extends the maximum altitude of the MPD from 6 to 8 km and substantially increases the accuracy of the WV retrievals starting above 2 km. PTV-MPD achieves the improvement by simultaneously denoising the MPD noisy observations and inferring the WV by separating the random noise from the non-random WV. An analysis with 130 radiosonde (RS) comparisons shows that the relative root-mean-square difference (RRMSE) of WV measurements between RS and PTV-MPD exceeds 100 % between 6 and 8 km, whereas the RRMSE between RS and the standard method exceeds 100 % near 3 km. In addition, we show that by employing PTV-MPD, the MPD is able to extend its useful range of WV estimates beyond that of the ARM Southern Great Plains Raman lidar (RRMSE exceeding 100 % between 3 and 4 km); the Raman lidar has a power-aperture product 500 times greater than that of the MPD.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

A differentiable, physics-informed ecosystem modeling and learning framework for large-scale inverse problems: demonstration with photosynthesis simulations

Photosynthesis plays an important role in carbon, nitrogen, and water cycles. Ecosystem models for photosynthesis are characterized by many parameters that are obtained from limited in situ measurements and applied to the same plant types. Previous site-by-site calibration approaches could not leverage big data and faced issues like overfitting or parameter non-uniqueness. Here we developed an end-to-end programmatically differentiable (meaning gradients of outputs to variables used in the model can be obtained efficiently and accurately) version of the photosynthesis process representation within the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) model. As a genre of physics-informed machine learning (ML), differentiable models couple physics-based formulations to neural networks (NNs) that learn parameterizations (and potentially processes) from observations, here photosynthesis rates. We first demonstrated that the framework was able to correctly recover multiple assumed parameter values concurrently using synthetic training data. Then, using a real-world dataset consisting of many different plant functional types (PFTs), we learned parameters that performed substantially better and greatly reduced biases compared to literature values. Further, the framework allowed us to gain insights at a large scale. Our results showed that the carboxylation rate at 25 °C (V c,max25 ) was more impactful than a factor representing water limitation, although tuning both was helpful in addressing biases with the default values. This framework could potentially enable substantial improvement in our capability to learn parameters and reduce biases for ecosystem modeling at large scales.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Dynamics at the serine loop underlie differential affinity of cryptochromes for CLOCK:BMAL1 to control circadian timing

Mammalian circadian rhythms are generated by a transcription-based feedback loop in which CLOCK:BMAL1 drives transcription of its repressors (PER1/2, CRY1/2), which ultimately interact with CLOCK:BMAL1 to close the feedback loop with ~24 hr periodicity. Here we pinpoint a key difference between CRY1 and CRY2 that underlies their differential strengths as transcriptional repressors. Both cryptochromes bind the BMAL1 transactivation domain similarly to sequester it from coactivators and repress CLOCK:BMAL1 activity. However, we find that CRY1 is recruited with much higher affinity to the PAS domain core of CLOCK:BMAL1, allowing it to serve as a stronger repressor that lengthens circadian period. We discovered a dynamic serine-rich loop adjacent to the secondary pocket in the photolyase homology region (PHR) domain that regulates differential binding of cryptochromes to the PAS domain core of CLOCK:BMAL1. Notably, binding of the co-repressor PER2 remodels the serine loop of CRY2, making it more CRY1-like and enhancing its affinity for CLOCK:BMAL1.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

A molecular mechanism for the generation of ligand-dependent differential outputs by the epidermal growth factor receptor

The epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase that couples the binding of extracellular ligands, such as EGF and transforming growth factor-α (TGF-α), to the initiation of intracellular signaling pathways. EGFR binds to EGF and TGF-α with similar affinity, but generates different signals from these ligands. To address the mechanistic basis of this phenomenon, we have carried out cryo-EM analyses of human EGFR bound to EGF and TGF-α. We show that the extracellular module adopts an ensemble of dimeric conformations when bound to either EGF or TGF-α. The two extreme states of this ensemble represent distinct ligand-bound quaternary structures in which the membrane-proximal tips of the extracellular module are either juxtaposed or separated. EGF and TGF-α differ in their ability to maintain the conformation with the membrane-proximal tips of the extracellular module separated, and this conformation is stabilized preferentially by an oncogenic EGFR mutation. Close proximity of the transmembrane helices at the junction with the extracellular module has been associated previously with increased EGFR activity. Our results show how EGFR can couple the binding of different ligands to differential modulation of this proximity, thereby suggesting a molecular mechanism for the generation of ligand-sensitive differential outputs in this receptor family.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

Passive millimeter wave differential interference contrast polarimetry

Differential polarization imaging systems include an axicon configured to provide a displacement of ray bundles associated with different image patches. The displaced ray bundles are directed to antenna horns and orthomode transducers so as to provide outputs correspond to orthogonal linear states of polarization (SOPs). The outputs are directed to a differential radiometer so that Stokes parameter differences between image patches can be obtained. The ray bundle displacements can be selected to correspond to a mechanical spacing of antenna horns. In some examples, ray bundle displacement corresponds to a displacement less than the diffraction limit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Aberration-corrected X-ray spectrum imaging and Fresnel contrast to differentiate nanoclusters and cavities in helium-irradiated alloy 14YWT

Helium accumulation negatively impacts structural materials used in neutron-irradiated environments, such as fission and fusion reactors. Next-generation fission and fusion reactors will require structural materials, such as steels, resistant to large neutron doses yet see service temperatures in the range most affected by helium embrittlement. Previous work has indicated the difficulty of experimentally differentiating nanometer-sized helium bubbles from the Ti-Y-O rich nanoclustsers (NCs) in radiation-tolerant nanostructured ferritic alloys (NFAs). Because the NCs are expected to sequester helium away from grain boundaries and reduce embrittlement, experimental methods to study simultaneously the NC and bubble populations are needed. In this study, aberration-corrected scanning transmission electron microscopy (STEM) results combining high-collection-efficiency X-ray spectrum images (SIs), multivariate statistical analysis (MVSA), and Fresnel-contrast bright-field STEM imaging have been used for such a purpose. Results indicate that Fresnel-contrast imaging, with careful attention to TEM-STEM reciprocity, differentiates bubbles from NCs, and MVSA of X-ray SIs unambiguously identifies NCs. Therefore, combined Fresnel-contrast STEM and X-ray SI is an effective STEM-based method to characterize helium-bearing NFAs.

Miller, Michael K↗

DOE OSTI2015

Low-voltage differentially-signaled modulators

Photonic modulators and methods of modulating an input optical signal are provided. A photonic modulator includes at least one modulator section and differential drive circuitry. The at least one modulator section includes a P-type layer and an N-type layer forming a PN junction in the modulator section. The differential drive circuitry is electrically coupled to the P-type layer and the N-type layer of the at least one modulator section.

14 SOLAR ENERGY↗

DOE OSTI2015

Differentially pumped dual linear quadrupole ion trap mass spectrometer

The present disclosure provides a new tandem mass spectrometer and methods of using the same for analyzing charged particles. The differentially pumped dual linear quadrupole ion trap mass spectrometer of the present disclose includes a combination of two linear quadrupole (LQIT) mass spectrometers with differentially pumped vacuum chambers.

47 OTHER INSTRUMENTATION↗

DOE OSTI2015

Electric wind in a Differential Mobility Analyzer

Electric wind -- the movement of gas, induced by ions moving in an electric field -- can be a distorting factor in size distribution measurements using Differential Mobility Analyzers (DMAs). The aim of this study was to determine the conditions under which electric wind occurs in the locally-built VLDMA (Very Long Differential Mobility Analyzer) and TSI Long-DMA (3081) and to describe the associated distortion of the measured spectra. Electric wind proved to be promoted by the increase of electric field strength, aerosol layer thickness, particle number concentration and particle size. The measured size spectra revealed three types of distortion: widening of the size distribution, shift of the mode of the distribution to smaller diameters and smoothing out the peaks of the multiply charged particles. Electric wind may therefore be a source of severe distortion of the spectrum when measuring large particles at high concentrations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Differentially pumped dual linear quadrupole ion trap mass spectrometer

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Measurement of the Pole Mass of the Top Quark using Differential $t\bar{t}$ Cross Sections in $p\bar{p}$ Collisions at $\sqrt{s}$ = 1.96 TeV

The differential $t\bar{t}$ cross sections, measured as a function of the transverse momentum of the top quark and the invariant mass of the $t\bar{t}$ system, are employed to determine the pole mass of the top quark. The data corresponds to an integrated luminosity of 9.7 $fb^{-1}$, collected with the D0 detector of the Fermilab Tevatron. Precise calculations at next-to-next-to leading order in perturbative quantum chromodynamics provide the absolute differential cross sections that are employed to extract the pole mass of the top quark.We measure the pole mass of the top quark to be 169.1 ± 2.5 (tot.) GeV.

Czakon, M.↗

DOE OSTI2018

Gas stream analysis using voltage-current time differential operation of electrochemical sensors

A method for analysis of a gas stream. The method includes identifying an affected region of an affected waveform signal corresponding to at least one characteristic of the gas stream. The method also includes calculating a voltage-current time differential between the affected region of the affected waveform signal and a corresponding region of an original waveform signal. The affected region and the corresponding region of the waveform signals have a sensitivity specific to the at least one characteristic of the gas stream. The method also includes generating a value for the at least one characteristic of the gas stream based on the calculated voltage-current time differential.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

CHEMNODE: CHEMICAL KINETICS SOLVER APPROACH BASED ON NEURAL ORDINARY DIFFERENTIAL EQUATIONS

This software contains an algorithm to model and predict the time evolution of chemical kinetics in reacting flow simulations using neural ordinary differential equations (NODEs). The approach works by using artificial neural networks to predict the chemical source terms. It achieves this by using forward-mode automatic differentiation and the Levenberg-Marquardt algorithm to adjust the neural network parameters, such that the discrepancies between the actual and predicted species profiles are minimized.

OWOYELE, OPEOLUWA↗

DOE OSTI2022

New directions for surrogate models and differentiable programming for High Energy Physics detector simulation

The computational cost for high energy physics detector simulation in future experimental facilities is going to exceed the current available resources. To overcome this challenge, new ideas on surrogate models using machine learning methods are being explored to replace computationally expensive components. Additionally, differentiable programming has been proposed as a complementary approach, providing controllable and scalable simulation routines. In this document, new and ongoing efforts for surrogate models and differential programming applied to detector simulation are discussed in the context of the 2021 Particle Physics Community Planning Exercise (`Snowmass').

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗