Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Inference mechanisms”

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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integrating biological knowledge for mechanistic inference in the host-associated microbiome

Advances in high-throughput technologies have enhanced our ability to describe microbial communities as they relate to human health and disease. Alongside the growth in sequencing data has come an influx of resources that synthesize knowledge surrounding microbial traits, functions, and metabolic potential with knowledge of how they may impact host pathways to influence disease phenotypes. These knowledge bases can enable the development of mechanistic explanations that may underlie correlations detected between microbial communities and disease. In this review, we survey existing resources and methodologies for the computational integration of broad classes of microbial and host knowledge. We evaluate these knowledge bases in their access methods, content, and source characteristics. We discuss challenges of the creation and utilization of knowledge bases including inconsistency of nomenclature assignment of taxa and metabolites across sources, whether the biological entities represented are rooted in ontologies or taxonomies, and how the structure and accessibility limit the diversity of applications and user types. We make this information available in a code and data repository at: https://github.com/lozuponelab/knowledge-source-mappings. Addressing these challenges will allow for the development of more effective tools for drawing from abundant knowledge to find new insights into microbial mechanisms in disease by fostering a systematic and unbiased exploration of existing information.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Deep learning of dynamically responsive chemical Hamiltonians with semiempirical quantum mechanics

Conventional machine-learning (ML) models in computational chemistry learn to directly predict molecular properties using quantum chemistry only for reference data. While these heuristic ML methods show quantum-level accuracy with speeds several orders of magnitude faster than traditional quantum chemistry methods, they suffer from poor extensibility and transferability; i.e., their accuracy degrades on large or new chemical systems. Incorporating quantum chemistry frameworks into the ML models directly solves this problem. Here we take the structure of semiempirical quantum mechanics (SEQM) methods to construct dynamically responsive Hamiltonians. SEQM methods use empirical parameters fitted to experimental properties to construct reduced-order Hamiltonians, facilitating much faster calculations than ab initio methods but with compromised accuracy. By replacing these static parameters with machine-learned dynamic values inferred from the local environment, we greatly improve the accuracy of the SEQM methods. Trained on molecular energies and atomic forces, these dynamically generated Hamiltonian parameters show a strong correlation with atomic hybridization and bonding. Trained with only about 60,000 small organic molecular conformers, the resulting model retains interpretability, extensibility, and transferability when testing on much larger chemical systems and predicting various molecular properties. Overall, this work demonstrates the virtues of incorporating physics-based descriptions with ML to develop models that are simultaneously accurate, transferable, and interpretable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Transactive Energy System Deployment Over Insecure Communication Links

Here, in this paper, the privacy and security issues associated with the transactive energy system (TES) deployment over insecure communication links are addressed. In particular, it is ensured that 1) individual agents’ bidding information is kept private throughout hierarchical market-based interactions; and 2) any extraneous data injection attack can be quickly and easily detected. An implementation framework is proposed to enable the cryptography-based enhancement of privacy and security for the deployment of any general hierarchical systems including TESs. Under the proposed framework, a unified cryptography-based approach is developed to achieve both privacy and security simultaneously. Specifically, privacy preservation is realized by an enhanced Paillier encryption scheme, where a block design is proposed to significantly improve computational efficiency. Attack detection is further achieved by an enhanced Paillier digital signature scheme, where a stamp-concatenation mechanism is proposed to enable detection of data replace and reorder attacks. Simulation results verify the effectiveness of the proposed cyber-resilient design for transactive energy systems. Note to Practitioners—This paper is motivated by addressing the issues of cyber resiliency for practically deploying transactive energy system (TES) but it is also applicable to the problem of enhancing the privacy and security for any general hierarchical control systems. TES is an emerging control approach that engages energy suppliers and customers through market operations and uses the price to optimally allocate energy resources. While it has been shown to be promising for power system applications, the underlying market-based interactions raise significant concerns of privacy (data leakage) and security (data tampering). However, existing TES works only focus on the coordination mechanism instead of privacy and security issues. This paper proposes a new cryptography-based TES design for practical deployment. Specifically, to protect privacy, individual supply and demand amounts to be exchanged are all encrypted in a particular way such that the original amounts cannot be inferred from the encrypted amounts, while the desired computation for setting the market clearing price can be carried out over the encrypted amounts, thus generating an encrypted result which, when decrypted, matches that of the same computation over the original amounts. To achieve security, for each exchanged data, its sender generates a particular digital signature which is exchanged together with the data. This enables the receiver to automatically detect the integrity by checking whether a mathematical relationship holds for the pair of data and signature. In our future research, we will investigate more challenging scenarios where some suppliers and customers themselves could be corrupted and purposely submit distorted amounts.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Zonal superrotation above Venus' cloud base induced by the semidiurnal tide and the mean meridional circulation

The equilibrium zonal wind structure resulting from the interaction of the semidiurnal tide and the mean meridional circulation driven by the zonally averaged solar heating above the Venus cloud base were calculated. The results show that the tidal mechanism proposed by Fels and Lindzen (1974) can account for a substantial fraction (and possibly all) of the increase of the equatorial wind speed above the cloud base. Above the cloud tops, tidal deceleration may be too small to produce the zonal wind decrease with height inferred from thermal data. Tidal forcing does not explain the superrotation below the clouds, and additional eddy sources are needed to account for the zonal wind structure at mid and high latitudes.

Hou, Arthur Y.↗
NASA NTRS1997

Mapping the Solar Wind from its Source Region into the Outer Corona

Knowledge of the radial variation of the plasma conditions in the coronal source region of the solar wind is essential to exploring coronal heating and solar wind acceleration mechanisms. The goal of the proposal was to determine as many plasma parameters in the solar wind acceleration region and beyond as possible by coordinating different observational techniques, such as Interplanetary Scintillation Observations, spectral line intensity observations, polarization brightness measurements and X-ray observations. The inferred plasma parameters were then used to constrain solar wind models.

Esser, Ruth↗
NASA NTRS2001

Icehouse Effect: A Selective Arctic Cooling Trend Current Models are Missing

The icehouse effect is a hypothesized climate feedback mechanism which could result in human-caused surface cooling trends in polar regions. Once understood in detail, it becomes apparent that these trends, which are discernable in the literature, but have been largely dismissed, do not conflict with the consensus assessment of the evidence, which infers century-scale Arctic warming. In fact, confirmation of the hypothesis would substantially strengthen the argument that there is a detectable human influence on today's climate. This apparent enigma is resolved only through careful attention to the detail of the hypothesis and the data supporting it. The posited surface cooling is entirely dependent on the existence of climate warming in layers capping the stable boundary layer. Also, the cooling is not pandemic, but is selective. It is readily revealed in properly sorted data by making use of the principles of micrometeorological similarity. Specifically, the cooling is manifest under a range of favorable turbulence conditions which can develop and disappear locally on time scales of minutes to hours because of the intrinsically intermittent nature of stable boundary layer turbulence. Because of the fine-scale nature of the processes which produce the cooling, modeling it is a difficult proposition. Vertical resolution on the order of 1 meter is required. Adequate models of intermittent surface fluxes coupled with radiation exchange do not currently exist, not as parameterizations for aggregated systems, nor in large eddy simulation (LES) models. This presentation will introduce the theory. An important testable null hypothesis emerges: the icehouse effect produces a unique signature or "fingerprint" which could not be produced by any other known process. The presence of this signature will be demonstrated using nearly all available Arctic temperature observations. Its aggregate effect is clearly found in Arctic monthly surface temperature trends when sorted by climatological stability. Using all available Arctic rawinsonde ascents - about 1.1 million profiles, "frozen moments" of the icehouse processes are captured in various states. Because turbulent time scales are so short in the stable boundary layer. each of these snapshots can be treated as independent -- their chronology is irrelevant. Micrometeorological similarity is invoked to reassemble the soundings into bins of similar stability and it is in a wide, coherent range of these stability bins where the cooling effect is revealed.

Wetzel, Peter J.↗
DOE OSTI2023

Noise-specific beating in the higher-level Ramsey curves of a transmon qubit

We report: in the higher levels of superconducting transmon devices and more generally charge sensitive devices, T 2 * measurements made in the presence of low-frequency time-correlated 1/f charge noise and quasiparticle-induced parity flips can give an underestimation of the total dephasing time. The charge variations manifest as beating patterns observed in the overlay of several Ramsey fringe curves and are reproduced with a phenomenological Ramsey curve model, which accounts for the charge variations. T 2 * dephasing times, which more accurately represent the total dephasing time, are obtained. The phenomenological model is compared with a Lindblad master equation model. Both models are found to be in agreement with one another and the experimental data. Finally, the phenomenological formulation enables a simple method in which the power spectral density for the low-frequency noise can be inferred from the overlay of several Ramsey curves.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Neural Density Estimation and Uncertainty Quantification for ChemCam Spectra [Slides]

The ChemCam instrument of Curiosity uses laser-induced breakdown spectroscopy (LIBS). It fires a laser at target and vaporizes rock surfaces, creating a plasma. Three spectrographs divide the plasma light into wavelengths for chemical analysis: ultraviolet, violet, and visible near-infrared. Regression methods (SVR, PCR, CNN) have been employed for calibration (prediction of the elemental composition of samples); however, labeled ChemCam samples are limited. Here, we focus on unsupervised learning and employ generative models from ChemCam analysis. Further, we use labels (supervised) in combination to the generative model to compute uncertainties related to predictions. We report generative modeling can be successfully applied to model real-world data. Normalizing flow models can be efficiently constructed on latent spaces for fast downstream inference. Unsupervised and supervised learning can be combined to form an uncertainty quantification framework.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Cometary Activity Begins at Kuiper Belt Distances: Evidence from C/2017 K2

We study the development of activity in the incoming long-period comet C/2017 K2 over the heliocentric distance range 9 ≲ r {sub H} ≲ 16 au. The comet continues to be characterized by a coma of submillimeter-sized and larger particles ejected at low velocity. In a fixed co-moving volume around the nucleus we find that the scattering cross section of the coma, C, is related to the heliocentric distance by a power law, C∝r{sub H}{sup -s}, with heliocentric index s = 1.14 ± 0.05. This dependence is significantly weaker than the r {sub H} {sup -2} variation of the insolation as a result of two effects. These are, first, the heliocentric dependence of the dust velocity and, second, a lag effect due to very slow-moving particles ejected long before the observations were taken. A Monte Carlo model of the photometry shows that dust production beginning at r {sub H} ~ 35 au is needed to match the measured heliocentric index, with only a slight dependence on the particle size distribution. Mass-loss rates in dust at 10 au are of order 10{sup 3} kg s{sup -1}, while loss rates in gas may be much smaller, depending on the unknown dust to gas ratio. Consequently, the ratio of the nongravitational acceleration to the local solar gravity, α', may, depending on the nucleus size, attain values of ~10{sup -7} ≲ α' ≲ 10{sup -5}, comparable to values found in short-period comets at much smaller distances. Nongravitational acceleration in C/2017 K2 and similarly distant comets, while presently unmeasured, may limit the accuracy with which we can infer the properties of the Oort cloud from the orbits of long-period comets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1993

Thermal conductivity measurements of particulate materials under Martian conditions

The mean particle diameter of surficial units on Mars has been approximated by applying thermal inertia determinations from the Mariner 9 Infrared Radiometer and the Viking Infrared Thermal Mapper data together with thermal conductivity measurement. Several studies have used this approximation to characterize surficial units and infer their nature and possible origin. Such interpretations are possible because previous measurements of the thermal conductivity of particulate materials have shown that particle size significantly affects thermal conductivity under martian atmospheric pressures. The transfer of thermal energy due to collisions of gas molecules is the predominant mechanism of thermal conductivity in porous systems for gas pressures above about 0.01 torr. At martian atmospheric pressures the mean free path of the gas molecules becomes greater than the effective distance over which conduction takes place between the particles. Gas particles are then more likely to collide with the solid particles than they are with each other. The average heat transfer distance between particles, which is related to particle size, shape and packing, thus determines how fast heat will flow through a particulate material.The derived one-to-one correspondence of thermal inertia to mean particle diameter implies a certain homogeneity in the materials analyzed. Yet the samples used were often characterized by fairly wide ranges of particle sizes with little information about the possible distribution of sizes within those ranges. Interpretation of thermal inertia data is further limited by the lack of data on other effects on the interparticle spacing relative to particle size, such as particle shape, bimodal or polymodal mixtures of grain sizes and formation of salt cements between grains. To address these limitations and to provide a more comprehensive set of thermal conductivities vs. particle size a linear heat source apparatus, similar to that of Cremers, was assembled to provide a means of measuring the thermal conductivity of particulate samples. In order to concentrate on the dependence of the thermal conductivity on particle size, initial runs will use spherical glass beads that are precision sieved into relatively small size ranges and thoroughly washed.

Presley, M. A.↗
DOE OSTI2026

Segmentation method comparison for residual fiber length measurement across tiled microscopy images

Fiber length distribution (FLD), in part, governs mechanical properties in discontinuous fiber composites, yet manual measurement methods limit the high-throughput characterization needed for materials design optimization. This study compares deep learning segmentation approaches for automated FLD measurement in large-field microscopy, evaluating how method choice affects the microstructural descriptors used in structure-property-processing relationships. A critical challenge is that high-resolution microscopy images (10,000×10,000 pixels) must be tiled for deep learning analysis, fragmenting fibers at boundaries. We demonstrate that segmentation method proves crucial for measurement accuracy. For example, instance segmentation with Slicing Aided Hyper Inference (SAHI) preserves individual fiber integrity across tiles while semantic segmentation prioritizes speed. Comparing against manual measurement of extracted carbon fibers, YOLOv11-SAHI matched manual ground truth (238 μm weighted mean) with 40x speedup (4.5 vs 167 minutes per image). U-Net provides rapid quantification although it is at the cost of reduced accuracy due only reliably measuring stand-alone fibers. Our comparative analysis reveals that instance segmentation with SAHI better preserves length measurements while semantic segmentation prioritizes speed, providing empirical guidance for method selection. The characterization provides essential inputs for mechanical property prediction models and inverse design workflows, accelerating composite materials development cycles.

Additive manufacturing↗
NASA NTRS1989

Radial diffusion in the Uranian radiatian belts - Inferences from satellite absorption loss models

Low-energy charged particle (LECP) phase space density profiles available from the Voyager/1986 Uranus encounter are analyzed, using solutions of the time-averaged radial diffusion equation for charged particle transport in a dipolar planetary magnetic field. Profiles for lower-energy protons and electrons are first analyzed to infer radial diffusion rate as a function of L, assuming that satellite absorption is the dominant loss process and local sources for these particles are negligible. Satellite macrosignatures present in the experimentally derived profiles are approximately reproduced in several cases, lending credence to the loss model and indicating that magnetospheric distributed losses are not as rapid as satellite absorption near the minimum satellite L shells for the particles. Diffusion rates and L dependences are found to be similar to those previously inferred in the inner Jovian magnetosphere (Thomsen et al., 1977) and for the inner Saturnian magnetosphere (Hood, 1985). Profiles for higher energy electrons and protons are also analyzed using solutions that allow for the existence of significant particle sources as well as sinks. Possible implications for radial diffusion mechanisms in the Uranian radiation belts are discussed.

Hood, L. L.↗
NASA NTRS1991

Molecular line emission models of Herbig-Haro objects. I - H2 emission

A comprehensive model for molecular hydrogen emssion in Herbig-Haro objects that are associated with the heads of radiative stellar jets is presented by using a simple representation of the jet head as a comprising a leading bow shock and a trailing jet shock, separated by a dense layer of cool shocked gas. Attention is given to collisional excitation in a nondissociative shock and formation pumping in the molecular reformation zone behind a dissociative shock, employing detailed shock and photodissociation-region emission models that incorporate most of the relevant atomic physics and chemistry. The conditions under which each of these excitation mechanisms may be expected to contribute to the observed emission are discussed, and a general diagnostic scheme for discriminating among them is constructed. Applying this scheme to the HH 1-2 system, strong evidence for excitation by the radiation field of a fast shock is found. It is inferred that FUV pumping contributes a significant fraction of the H2 line emission, and it is shown that this can occur only if the UV pump lines are not strongly self-shielded.

Wolfire, Mark G.↗
NASA NTRS2010

Vestibular-Somatosensory Convergence in Head Movement Control During Locomotion after Long-Duration Space Flight

Exposure to the microgravity conditions of space flight induces adaptive modification in the control of vestibular-mediated reflexive head movement during locomotion after space flight. Space flight causes astronauts to be exposed to somatosensory adaptation in both the vestibular and body load-sensing (BLS) systems. The goal of these studies was to examine the contributions of vestibular and BLS-mediated somatosensory influences on head movement control during locomotion after long-duration space flight. Subjects were asked to walk on a treadmill driven at 1.8 m/s while performing a visual acuity task. Data were collected using the same testing protocol from three independent subject groups; 1) normal subjects before and after exposure to 30 minutes of 40% bodyweight unloaded treadmill walking, 2) bilateral labyrinthine deficient (LD) patients and 3) astronauts who performed the protocol before and after long duration space flight. Motion data from head and trunk segmental motion data were obtained to calculate the angular head pitch (HP) movements during walking trials while subjects performed the visual task, to estimate the contributions of vestibular reflexive mechanisms in HP movements. Results showed that exposure to unloaded locomotion caused a significant increase in HP movements, whereas in the LD patients the HP movements were significantly decreased. Astronaut subjects results showed a heterogeneous response of both increases and decreases in the amplitude of HP movement. We infer that BLS-mediated somatosensory input centrally modulates vestibular input and can adaptively modify head-movement control during locomotion. Thus, space flight may cause a central adaptation mediated by the converging vestibular and body load-sensing somatosensory systems.

Mulavara, Ajitkumar↗
DOE OSTI2022

Regulators of early maize leaf development inferred from transcriptomes of laser capture microdissection (LCM)-isolated embryonic leaf cells

The superior photosynthetic efficiency of C 4 leaves over C 3 leaves is owing to their unique Kranz anatomy, in which the vein is surrounded by one layer of bundle sheath (BS) cells and one layer of mesophyll (M) cells. Kranz anatomy development starts from three contiguous ground meristem (GM) cells, but its regulators and underlying molecular mechanism are largely unknown. To identify the regulators, we obtained the transcriptomes of 11 maize embryonic leaf cell types from five stages of pre-Kranz cells starting from median GM cells and six stages of pre-M cells starting from undifferentiated cells. Principal component and clustering analyses of transcriptomic data revealed rapid pre-Kranz cell differentiation in the first two stages but slow differentiation in the last three stages, suggesting early Kranz cell fate determination. In contrast, pre-M cells exhibit a more prolonged transcriptional differentiation process. Differential gene expression and coexpression analyses identified gene coexpression modules, one of which included 3 auxin transporter and 18 transcription factor (TF) genes, including known regulators of Kranz anatomy and/or vascular development. In situ hybridization of 11 TF genes validated their expression in early Kranz development. We determined the binding motifs of 15 TFs, predicted TF target gene relationships among the 18 TF and 3 auxin transporter genes, and validated 67 predictions by electrophoresis mobility shift assay. From these data, we constructed a gene regulatory network for Kranz development. Our study sheds light on the regulation of early maize leaf development and provides candidate leaf development regulators for future study.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1981

Inferences about the solar wind dynamics from observed distributions of electrons and ions

Recent measurements, mostly from Helios and Voyager, were reviewed. The observational material was compiled into a series of radial profiles for various macroscopic plasma parameters. Several examples for experimentally determined three-dimensional distribution functions of protons are shown. The physical properties of the solar wind electrons were surveyed. The still unresolved question of the driving mechanism of the solar wind is considered. The problem of the energy balance in pure, high velocity streams emanating from solar coronal holes was outlined. It is suggested that the suprathermal electrons may play an important role in driving the wind. Numerical estimates, referring to the lower corona, are offered in support of this hypothesis.

Olbert, S.↗
DOE OSTI2026

In-situ sensor monitoring of multi-class gas porosity formation in laser powder bed fusion using convolutional neural network

In-situ monitoring of defect formation remains a significant challenge in the laser powder bed fusion (LPBF) process. Recent advances have enabled real-time defect detection with machine learning and in-situ sensing technologies; however, most studies focus on binary classification of keyhole pores, limiting nuanced multi-class pore differentiation and formation mechanisms. This work introduces a multi-class pore detection framework (no pore, small pores < 15 µm, and large pores > 15 µm) by leveraging photodiode sensor data alongside high-fidelity synchrotron X-ray imaging. The 15 µm threshold is selected to distinguish between two fundamentally different defect mechanisms, following the physical size-mechanism boundary established by prior high-resolution synchrotron X-ray characterization of Al6061 LPBF. Distinguishing these classes is critical because large keyhole pores are structurally detrimental, whereas small gas pores are often benign, requiring different process control strategies. Thermal emission monitoring data collected simultaneously with high-speed X-ray imaging at the Stanford Synchrotron Radiation Lightsource (SSRL), are correlated with subsurface melt pool dynamics to establish ground truth. Continuous Wavelet Transform (CWT) with optimized parameters converts the photodiode time-series signals into time–frequency images, facilitating feature extraction. Convolutional Neural Networks (CNN) are then applied for real-time multi-class pore classification in an average inference time of 1 ms per signal window. It achieves 79% accuracy and an Area Under the Receiver Operating Characteristic curve (AUC ROC) score of 0.89 with five-fold cross-validation. The results demonstrate that coupling CWT-based feature engineering with CNN architecture enables reliable multi-class pore detection in Al6061 builds using affordable in-situ sensors. This approach advances scalable and affordable quality assurance in additive manufacturing by moving beyond binary defect detection toward more nuanced classification of porosity mechanisms with in-situ sensors and machine learning.

Laser powder bed fusion, Multi-class pores, In-sit↗
DOE OSTI2026

Emergent anisotropic three-phase order in critically doped superconducting diamond films

Two decades since its discovery, superconducting heavily boron-doped diamond (HBDD) still poses fundamental questions that need to be answered to unlock its full potential for quantum applications. We use electrical magnetotransport measurements of critically doped homoepitaxial single crystal HBDD films to reveal signatures of intrinsically granular superconductivity. By studying the dependence of electrical resistivity on temperature and magnetic field vector, we infer that this granularity arises from doping induced disorder. We observe an unexpected three-phase anisotropy in the magnetoresistance, accompanied by a spontaneous transverse voltage (Hall anomaly). Our findings indicate the emergence of an anisotropic order in an otherwise isotropic single crystal HBDD film, offering insights into the mechanism of superconductivity in this quantum material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗