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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Extended ecosystem signatures with application to Eos synergism requirements

The primary objective is to define the advantages of synergistically combining optical and microwave remote sensing measurements for the determination of biophysical properties important in ecosystem modeling. This objective was approached in a stepwise fashion starting with ground-based observations of controlled agricultural and orchard canopies and progressing to airborne observations of more natural forest ecosystems. This observational program is complemented by a parallel effort to model the visible reflectance and microwave scattering properties of composite vegetation canopies. The goals of the modeling studies are to verify our basic understanding of the sensor-scene interaction physics and to provide the basis for development of inverse models optimized for retrieval of key biophysical properties. These retrieval algorithms can then be used to simulate the expected performance of various aspects of Eos including the need for simultaneous SAR and HIRIS observations or justification for other (non-synchronous) relative timing constraints and the frequency, polarization, and angle of incidence requirements for accurate biophysical parameter extractions. This program completed a very successful series of truck-mounted experiments, made remarkable progress in development and validation of optical reflectance and microwave scattering models for vegetation, extended the scattering models to accommodate discontinuous and periodic canopies, developed inversion approaches for surface and canopy properties, and disseminated these results widely through symposia and journal publications. In addition, the third generation of the computer code for the microwave scattering models was provided to a number of other US, Canadian, Australian, and European investigators who are currently presenting and publishing results using the MIMICS research code.

Ulaby, Fawwaz T.↗
NASA NTRS2006

System Would Detect Foreign-Object Damage in Turbofan Engine

A proposed data-fusion system, to be implemented mostly in software, would further process the digitized and preprocessed outputs of sensors in a turbofan engine to detect foreign-object damage (FOD) [more precisely, damage caused by impingement of such foreign objects as birds, pieces of ice, and runway debris]. The proposed system could help a flight crew to decide what, if any, response is necessary to complete a flight safely, and could aid mechanics in deciding what post-flight maintenance action might be needed. The sensory information to be utilized by the proposed system would consist of (1) the output of an accelerometer in an engine-vibration-monitoring subsystem and (2) features extracted from a gas path analysis. ["Gas path analysis" (GPA) is a term of art that denotes comprehensive analysis of engine performance derived from readings of fuel-flow meters, shaft-speed sensors, temperature sensors, and the like.] The acceleration signal would first be processed by a wavelet-transform-based algorithm, using a wavelet created for the specific purpose of finding abrupt FOD-induced changes in noisy accelerometer signals. Two additional features extracted would be the amplitude of vibration (determined via a single- frequency Fourier transform calculated at the rotational speed of the engine), and the rate of change in amplitude due to an FOD-induced rotor imbalance. This system would utilize two GPA features: the fan efficiency and the rate of change of fan efficiency with time. The selected GPA and vibrational features would be assessed by two fuzzy-logic inference engines, denoted the "Gas Path Expert" and the "Vibration Expert," respectively (see Figure 1). Each of these inference engines would generate a "possibility" distribution for occurrence of an FOD event: Each inference engine would assign, to its input information, degrees of membership, which would subsequently be transformed into basic probability assignments for the gas path and vibration components. The outputs of the inference engines would be fused by use of Dempster s combination algorithm (more precisely, an algorithm, based on the Dempster-Shafer-Yager theory of evidence, for fusing uncertain or imprecise information) to provide a reduced body of information to a human or computer decision maker. Figure 2 depicts some outputs generated in response to simulated accelerometer and GPA signals

Torso, James A.↗
NASA NTRS2014

The Aerodynamics of Axisymmetric Blunt Bodies Flying at Angle of Attack

The Mars Science Laboratory entry capsule is used as an example to demonstrate how a blunt body of revolution must be treated as asymmetric in some respects when flying at a non-zero trim angle of attack. A brief description of the axisymmetric moment equations are provided before solving a system of equations describing the lateral-directional moment equations for a blunt body trimming at an angle of attack. Simplifying assumptions are made which allow the solution to the equations to be rearranged to relate the roll and yaw stability with sideslip angle to the frequency of oscillation of the vehicle body rates. The equations show that for a blunt body the roll and yaw rates are in phase and proportional to each other. The ratio of the rates is determined by the static stability coefficients and mass properties about those axes. A trajectory simulation is used to validate the static yaw stability parameter identification equation and a simple method of identifying the oscillation frequency from the body rates. The approach is shown to successfully extract the modeled yaw stability coefficient along a simulated Mars entry in agreement with data earlier analysis of MSL flight data.

Schoenenberger, Mark↗
NASA NTRS2014

Experimental and Theoretical Study of Thermodynamics of the Reaction of Titania and Water at High Temperatures

The transpiration method was used to determine the volatility of titanium dioxide (TiO2) in water vapor-containing environments at temperatures between 1473 and 1673 K. Water contents ranged from 0 to 76 mole % in oxygen or argon carrier gases for 20 to 250 hr exposure times. Results indicate that oxygen is not a key contributor to volatilization and the primary reaction for volatilization in this temperature range is: TiO2(s) + H2O(g) = TiO(OH)2(g). Data were analyzed with both the second and third law methods to extract an enthalpy and entropy of formation. The geometry and vibrational frequencies of TiO(OH)2(g) were computed using B3LYP density functional theory, and the enthalpy of formation was computed using the coupled-cluster singles and doubles method with a perturbative correction for connected triple substitutions [CCSD(T)]. Thermal functions are calculated using both a structure with bent and linear hydroxyl groups. Calculated second and third heats show closer agreement with the linear hydroxyl group, suggesting more experimental and computational spectroscopic and structural work is needed on this system.

equilibrium↗
NASA NTRSDate not supplied

Fluid & Thermal Analysis of a Manifold Microchannel Heat Sink

A three-dimensional (3-D) numerical model has been developed to study the fluid flow and heat transfer through a manifold-microchannel (MMC) heat sink, a microfluidic cooling system designed as a heat dissipation solution for compact, high-powered electronic systems. An MMC consists of a 3-D manifold structure that distributes working fluid through alternating inlet and outlet manifold channels that guide the fluid to and from the microchannels, shortening the flow length and thereby, reducing the pressure drop across the system. Wide bandgap semiconductors such as silicon carbide (SiC) are increasingly utilized due to their ability to enable smaller electronic devices and components to operate more efficiently at higher frequencies. These semiconductors can greatly benefit from the MMC, which can extract all the heat produced by compact, high-powered electronics, enabling them to achieve optimal performance. The MMC also utilizes an embedded cooling approach which allows for fabrication directly within SiC-based electronics, resulting in significant mass and weight savings and lower thermal resistance than conventional heat sink designs. This paper outlines the methods used to conduct fluid and thermal analysis of different MMC configurations for flow parameters such as flow rate and inlet flow conditions. This study involves both steady state and transient thermal analysis as a gradually increasing heat flux is applied to the system over time, which is representative of the heat dissipation from the electronics over a given period. Results from the analysis show that the MMC is capable of effectively dissipating heat flux of ~100 W/cm2 while maintaining considerably low pressure drop (< 1 kPa) and thermal resistance (< 1 K/W) for certain single-phase working fluids.

manifold microchannel↗
NASA NTRSDate not supplied

Fluid & Thermal Analysis of a Manifold Microchannel Heat Sink

A three-dimensional (3-D) numerical model has been developed to study the fluid flow and heat transfer through a manifold-microchannel (MMC) heat sink, a microfluidic cooling system designed as a heat dissipation solution for compact, high-powered electronic systems. An MMC consists of a 3-D manifold structure that distributes working fluid through alternating inlet and outlet manifold channels that guide the fluid to and from the microchannels, shortening the flow length and thereby, reducing the pressure drop across the system. Wide bandgap semiconductors such as silicon carbide (SiC) are increasingly utilized due to their ability to enable smaller electronic devices and components to operate more efficiently at higher frequencies. These semiconductors can greatly benefit from the MMC, which can extract all the heat produced by compact, high-powered electronics, enabling them to achieve optimal performance. The MMC also utilizes an embedded cooling approach which allows for fabrication directly within SiC-based electronics, resulting in significant mass and weight savings and lower thermal resistance than conventional heat sink designs. This paper outlines the methods used to conduct fluid and thermal analysis of different MMC configurations for flow parameters such as flow rate and inlet flow conditions. This study involves both steady state and transient thermal analysis as a gradually increasing heat flux is applied to the system over time, which is representative of the heat dissipation from the electronics over a given period. Results from the analysis show that the MMC is capable of effectively dissipating heat flux of ~100 W/cm2 while maintaining considerably low pressure drop (< 1 kPa) and thermal resistance (< 1 K/W) for certain single-phase working fluids.

manifold microchannel↗
DOE OSTI2021

Analysis of mobility data to build contact networks for COVID-19

As social distancing policies and recommendations went into effect in response to COVID-19, people made rapid changes to the places they visit. These changes are clearly seen in mobility data, which records foot traffic using location trackers in cell phones. While mobility data is often used to extract the number of customers that visit a particular business or business type, it is the frequency and duration of concurrent occupancy at those sites that governs transmission. Understanding the way people interact at different locations can help target policies and inform contact tracing and prevention strategies. This paper outlines methods to extract interactions from mobility data and build networks that can be used in epidemiological models. Several measures of interaction are extracted: interactions between people, the cumulative interactions for a single person, and cumulative interactions that occur at particular businesses. Network metrics are computed to identify structural trends which show clear changes based on the timing of stay-at-home orders. Measures of interaction and structural trends in the resulting networks can be used to better understand potential spreading events, the percent of interactions that can be classified as close contacts, and the impact of policy choices to control transmission.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Hydrogen-Bond-Driven Chemical Separations: Elucidating the Interfacial Steps of Self-Assembly in Solvent Extraction

Chemical separations, particularly liquid extractions, are pervasive in academic and industrial laboratories, yet a mechanistic understanding of the events governing their function are obscured by interfacial phenomena that are notoriously difficult to measure. In this work, we investigate the fundamental steps of ligand self-assembly as driven by changes in the interfacial H-bonding network using vibrational sum frequency generation. Our results show how the bulk pH modulates the interfacial structure of extractants at the buried oil/aqueous interface via the formation of unique H-bonding networks that order and bridge ligands to produce self-assembled aggregates. These extended H-bonded structures are key to the subsequent extraction of Co2+ from the aqueous phase in promoting micelle formation and subsequent ejection of the said micelle into the oil phase. The combination of static and time-resolved measurements reveals the events underlying complexities of liquid extractions at high [Co2+]:[ligand] ratios by showing an evolution of interfacially assembled structures that are readily tuned on a chemical basis by altering the compositions of the aqueous phase. The results of this work point to new principles to design-applied separations through the manipulation of surface charge, electrostatic screening, and the associated H-bonding networks that arise at the interface to facilitate organization and subsequent extraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2009

Non-ambipolar radio-frequency plasma electron source and systems and methods for generating electron beams

An electron generating device extracts electrons, through an electron sheath, from plasma produced using RF fields. The electron sheath is located near a grounded ring at one end of a negatively biased conducting surface, which is normally a cylinder. Extracted electrons pass through the grounded ring in the presence of a steady state axial magnetic field. Sufficiently large magnetic fields and/or RF power into the plasma allow for helicon plasma generation. The ion loss area is sufficiently large compared to the electron loss area to allow for total non-ambipolar extraction of all electrons leaving the plasma. Voids in the negatively-biased conducting surface allow the time-varying magnetic fields provided by the antenna to inductively couple to the plasma within the conducting surface. The conducting surface acts as a Faraday shield, which reduces any time-varying electric fields from entering the conductive surface, i.e. blocks capacitive coupling between the antenna and the plasma.

Hershkowitz, Noah↗
NASA NTRS2011

Non-ambipolar radio-frequency plasma electron source and systems and methods for generating electron beams

An electron generating device extracts electrons, through an electron sheath, from plasma produced using RF fields. The electron sheath is located near a grounded ring at one end of a negatively biased conducting surface, which is normally a cylinder. Extracted electrons pass through the grounded ring in the presence of a steady state axial magnetic field. Sufficiently large magnetic fields and/or RF power into the plasma allow for helicon plasma generation. The ion loss area is sufficiently large compared to the electron loss area to allow for total non-ambipolar extraction of all electrons leaving the plasma. Voids in the negatively-biased conducting surface allow the time-varying magnetic fields provided by the antenna to inductively couple to the plasma within the conducting surface. The conducting surface acts as a Faraday shield, which reduces any time-varying electric fields from entering the conductive surface, i.e. blocks capacitive coupling between the antenna and the plasma.

Hershkowitz, Noah↗
DOE OSTI2022

A physics‐informed learning technique for fault location of DC microgrids using traveling waves

Abstract Fast and accurate fault location in DC power systems is of particular importance to ensure their reliable operation. One of the approaches for implementing a fast‐tripping protection scheme is to use Traveling waves (TW) initiated by a fault scenario. This paper proposes a physics‐informed machine learning approach that utilizes TWs for fault location in DC microgrids. TWs are extracted by the so‐called multiresolution analysis which identifies the TW's wavelet coefficients for multiple frequency ranges. This paper deploys Parseval's theorem to find the energy of wavelet coefficients as a quantitative metric for describing TWs. The hypothesis of this paper is that once the Parseval energy curves for a specific cable are extracted, they can be utilized to locate faults along with that cable regardless of the DC system in which the cable is deployed. The fault location algorithm uses Parseval energy curves to train a Gaussian Process (GP) estimator. With the Parseval energy values of measured current at the protection device location, the GP estimator is able to estimate fault locations with high accuracy. The effectiveness of the proposed algorithm is verified by simulating a DC microgrid system in PSCAD/EMTDC.

Paruthiyil, Sajay Krishnan↗
DOE OSTI2024

Performance Comparison of Machine Learning Models for Ultrasonic Nondestructive Evaluation of Alkali-Silica Reaction in Concrete

Alkali-silica reaction (ASR) causes concrete degradation, leading to cracking, rebar corrosion, and reduced structural integrity, which raises safety concerns. Ultrasonic nondestructive evaluation (NDE) effectively assesses concrete properties and monitors ASR progression. However, its deployment and analysis require specialized expertise and subjective interpretation. As computational power increases, artificial intelligence (AI) and machine learning (ML) algorithms are increasingly being used to automate NDE data analysis across various industries for AI-assisted automation. Regulatory agencies are adapting to this technological shift, prompting a need to evaluate current ML technologies’ capabilities and limitations in assessing concrete material properties and damage. This report presents a comparative analysis of four ML regression models for predicting concrete material damage induced by ASR expansion using long-term ultrasonic data monitoring. The models investigated include linear regression (LR), support vector regression (SVR), shallow neural networks (NN), and deep neural networks (DNN). LR, SVR, and shallow NN models use features extracted from ultrasonic signals, whereas the DNN model processes time-domain ultrasonic signals and frequency spectra directly. The study systematically compared the models’ performance from various perspectives, including model input, prediction performance, and generalization ability. The findings indicate significant variability in model performance, with some ML algorithms achieving very high or very low prediction accuracy depending on the preprocessing and feature engineering (extraction and selection) applied. Key insights include the observation that shallow ML models (LR, SVR, and shallow NNs) require meticulous preprocessing and feature extraction to achieve high accuracy. In contrast, the DNN model, although it bypasses the need for feature engineering, necessitates extensive preprocessing to mitigate noise and computational demands. The SVR model emerged as the top performer among the shallow models, and the DNN model exhibited superior performance on specific datasets but struggled with generalization across specimens from different batches. Additionally, the SVR model is sensitive to temperature variations, whereas the DNN model is robust in this regard. Using recurrent neural networks is recommended for future ASR expansion prediction studies. Recurrent neural networks’ inherent ability to capture temporal dependencies and long-term patterns makes them well suited for analyzing sequential ultrasonic monitoring data. Overall, the results and conclusions of this study could provide insights into the capabilities and effectiveness of ML when applied to ultrasonic NDE data and help identify best practices for using ML for ultrasonic NDE of concrete material properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Probing liquid/liquid interfaces at and away from equilibrium using vibrational sum frequency generation

The self-assembly and transport of species at oil/aqueous interfaces represent key mechanistic steps in processes spanning from liquid extraction to soft-matter neuromorphic electrical devices. While technologically and fundamentally important, there is a notable lack of chemical understanding regarding these buried interfaces due to challenges in differentiating species located at the surface from the nearby bulk phases. In this work, we will describe some of the challenges in probing chemistry at these liquid/liquid interfaces and detail the approaches we have developed using vibrational sum frequency generation to enable studies of these complex interfaces at and away from equilibrium. From these spectroscopic developments, new insight into solvation, ion pairing, aggregation, complexation, and transport will be discussed in the context of solvent extraction chemistry. Notably, we show how the presence of both oil and aqueous phases provides an environment to drive fundamentally different phenomena from what is observed at model air/aqueous interfaces. This difference arises from key differences in solvation and bulk populations that feedback onto the surface to drive emergent and often functional molecular assemblies.

Doughty, Benjamin L↗
NASA NTRS2013

The Atacama Cosmology Telescope: Likelihood for Small-Scale CMB Data

The Atacama Cosmology Telescope has measured the angular power spectra of microwave fluctuations to arcminute scales at frequencies of 148 and 218 GHz, from three seasons of data. At small scales the fluctuations in the primordial Cosmic Microwave Background (CMB) become increasingly obscured by extragalactic foregounds and secondary CMB signals. We present results from a nine-parameter model describing these secondary effects, including the thermal and kinematic Sunyaev-Zel'dovich (tSZ and kSZ) power; the clustered and Poisson-like power from Cosmic Infrared Background (CIB) sources, and their frequency scaling; the tSZ-CIB correlation coefficient; the extragalactic radio source power; and thermal dust emission from Galactic cirrus in two different regions of the sky. In order to extract cosmological parameters, we describe a likelihood function for the ACT data, fitting this model to the multi-frequency spectra in the multipole range 500 < l < 10000. We extend the likelihood to include spectra from the South Pole Telescope at frequencies of 95, 150, and 220 GHz. Accounting for different radio source levels and Galactic cirrus emission, the same model provides an excellent fit to both datasets simultaneously, with χ2/dof= 675/697 for ACT, and 96/107 for SPT. We then use the multi-frequency likelihood to estimate the CMB power spectrum from ACT in bandpowers, marginalizing over the secondary parameters. This provides a simplified 'CMB-only' likelihood in the range 500 < l < 3500 for use in cosmological parameter estimation

Cosmology↗
DOE OSTI2024

Investigation of coverage dependence of the stretching frequency of CO adsorbed on Pd surfaces at low coverage limits

The stretching frequency of the C—O bond is a sensitive probe of the local environment of a surface-bound CO molecule, including the adorption site and density, i.e. surface coverage. In this work, we extend our analysis beyond the frequency shift due to differences in adsorption configurations. Using density functional theory (DFT) calculations, we directly explore the correlations between surface coverage and the stretching frequency of adsorbed CO on Pd surfaces. Here we also perform constant pressure infrared reflection absorption measurements of CO on Pd(111) and use existing relations between pressure and coverage to derive coverage dependency. Both results are compared to previously reported experimental data. Our derived correlations of peak frequency and area with surface coverage can help interpret experimental IR spectra in real time and extract time-dependent concentration data from transient kinetic experiments.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS1993

Theoretical and simulated performance for a novel frequency estimation technique

A low complexity, open-loop, discrete-time, delay-multiply-average (DMA) technique for estimating the frequency offset for digitally modulated MPSK signals is investigated. A nonlinearity is used to remove the MPSK modulation and generate the carrier component to be extracted. Theoretical and simulated performance results are presented and compared to the Cramer-Rao lower bound (CRLB) for the variance of the frequency estimation error. For all signal-to-noise ratios (SNR's) above threshold, it is shown that the CRLB can essentially be achieved with linear complexity.

Crozier, Stewart N.↗
DOE OSTI2022

Transport of polymer-coated metal–organic framework nanoparticles in porous media

Abstract Injecting fluids into deep underground geologic structures is a critical component to development of long-term strategies for managing greenhouse gas emissions and facilitating energy extraction operations. Recently, we reported that metal–organic frameworks are low-frequency, absorptive-acoustic metamaterial that may be injected into the subsurface to enhance geophysical monitoring tools used to track fluids and map complex structures. A key requirement for this nanotechnology deployment is transportability through porous geologic media without being retained by mineral-fluid interfaces. We used flow-through column studies to estimate transport and retention properties of five different polymer-coated MIL-101(Cr) nanoparticles (NP) in siliceous porous media. When negatively charged polystyrene sulfonate coated nanoparticles (NP-PSS-70K) were transported in 1 M NaCl, only about 8.4% of nanoparticles were retained in the column. Nanoparticles coated with polyethylenimine (NP-PD1) exhibited significant retention (> 50%), emphasizing the importance of complex nanoparticle-fluid-rock interactions for successful use of nanofluid technologies in the subsurface. Nanoparticle transport experiments revealed that nanoparticle surface characteristics play a critical role in nanoparticle colloidal stability and as well the transport.

58 GEOSCIENCES↗
DOE OSTI2019

Diagnosis of Corrosion Process in Nuclear Power Plant Secondary Piping Structures

Corrosion inside secondary pipe structures in Nuclear Power Plants is difficult to detect without intrusion. Statistical and machine learning techniques are used to predict corrosion using pipe vibration data. 3D accelerometers were used to record pipe vibration data in three directions using six sensors. Vibration data were processed using the Hilbert-Huang Transformation, which is known for its adaptable basis function to non-linear and non-stationary signals. Hilbert-Huang Transformation using empirical mode functions generates multiple intrinsic mode functions of different amplitude and frequency levels from raw vibration data. From intrinsic mode functions features are extracted which include phase, energy, entropy, mean, standard deviation, skewness, and kurtosis. Logistic regression using only phase information correctly distinguished mass additions from baseline data in roughly 83% and 85% of the cases. Phase information varied substantially among different baseline runs and within trials of the same run. Random Forest resulted in >95% testing accuracy for both mass addition and mass removal data. Support Vector Machine had ~98% testing accuracy for mass removal and ~92% testing accuracy for mass additions when using Permutation Importance feature selection. When using Principle Component Analysis with Support Vector Machine, testing accuracy was ~68% testing accuracy for mass additions and ~85% testing accuracy for mass.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗