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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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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Structure constants in $ \mathcal{N} $ = 4 SYM at finite coupling as worldsheet g-function

We develop a novel nonperturbative approach to a class of three-point functions in planar $ \mathcal{N} $ N = 4 SYM based on Thermodynamic Bethe Ansatz (TBA). More specifically, we study three-point functions of a non-BPS single-trace operator and two determinant operators dual to maximal Giant Graviton D-branes in AdS 5 × S 5 . They correspond to disk one-point functions on the worldsheet and admit a simpler and more powerful integrability description than the standard single-trace three-point functions. We first introduce two new methods to efficiently compute such correlators at weak coupling; one based on large N collective fields, which provides an example of open-closed-open duality discussed by Gopakumar, and the other based on combinatorics. The results so obtained exhibit a simple determinant structure and indicate that the correlator can be interpreted as a generalization of g -functions in 2d QFT; an overlap between an integrable boundary state and a state corresponding to the single-trace operator. We then determine the boundary state at finite coupling using the symmetry, the crossing equation and the boundary Yang-Baxter equation. With the resulting boundary state, we derive the ground-state g -function based on TBA and conjecture its generalization to other states. This is the first fully nonperturbative proposal for the structure constants of operators of finite length. The results are tested extensively at weak and strong couplings. Finally, we point out that determinant operators can provide better probes of sub-AdS locality than single-trace operators and discuss possible applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Effect of second Si–O vibrational overtones/combinations on quantifying water in silicate and silica minerals using infrared spectroscopy, and an experimental method for its removal

Infrared spectroscopy (IR) is the most widely used analytical tool to quantify trace water in silicate and silica minerals. A prerequisite for highly accurate IR measurements of trace water is a good understanding of the effect of the second Si–O vibrational overtones/combination bands (2nd Si–O VOCBs) on the water peaks. Silicate and silica minerals can be divided as isolated (Q 0 ), paired (Q 1 ), ring (Q 2 ), chain (Q 1 or Q 2 ), sheet (Q 3 ) and framework (Q 4 ) structures according to the polymerization of their SiO 4 tetrahedral units, and the 2nd Si–O VOCBs of these different structural types attain different vibrational features which are expected to affect the water peaks to different extents. Here, we selected olivine (Q 0 ) and α-quartz (Q 4 ) as two endmember-like structural examples, performed extensive IR measurements on both pristine and heat-treated thin sections prepared for these two minerals, and explored the vibrational features of the 2nd Si–O VOCBs. In this work, we have found that the 2nd Si–O VOCBs are well separated from the water peaks in olivine, but severely overlap with the water peaks in α-quartz, confirming the different roles that the 2nd Si–O VOCBs play in quantifying trace water in silicate and silica minerals with different structural polymerizations. To remove the influence of the 2nd Si–O VOCBs (or any other species rather than water), an experimental protocol has been successfully developed, as approved by some fundamental equations and verified by the data of α-quartz in the literature. This development should lead to significant accuracy improvement in quantifying trace amounts of water in Earth and planetary materials.

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

Conclusions from 3 years of continuous capture plant operation without exchange of the AMP/PZ-based solvent at Niederaussem – insights into solvent degradation management

A many times heard mantra of solvent degradation management in amine-based post combustion capture is “keep the solvent clean” to minimize solvent consumption. It is assumed that the amine losses would decrease by the removal of metals, degradation products, and reactive trace components which are captured from the flue gas, like NO 2 (as potentially driving components of the amine degradation besides dissolved O 2 ). However, this theoretical hypothesis – based on results from laboratory experiments typically generated with fresh amines – disregards the complexity of the solvent matrix, interaction of potential metal catalysts with degradation products and oxidizing agents, and specific chemical requirements which must be fulfilled before a degradation mechanism can proceed. Degradation of the solvent CESAR1 (aqueous solution of 3.0 molar 2-amino-2-methylpropan-1-ol (AMP) and 1.5 molar piperazine (PZ)) is investigated in a unique long-time test campaign (testing time up to now 40 months; 24/7 operation) without replacement of the solvent inventory at the capture pilot plant at the lignite-fired power plant in Niederaussem. Three solvent management strategies with different effect mechanisms are investigated and evaluated: (a) removal of only anionic compounds and trace elements (within 75 days solvent inventory treated two times) and anionic as well as cationic compounds and trace elements (114 days, inventory treated four times) from the solvent by ion exchange, (b) adsorptive removal of trace elements from the solvent by active carbon in 35% of the operating time, and (c) removal of >80% NO 2 by flue gas pretreatment with thiosulfate/sulfite solution (dosing for 2,000 h). The results of the testing program clearly show that “solvent cleanliness” is not a well-defined parameter and that results from laboratory tests, tests without fully representative industrial flue gasses, and short-term testing of monoethanolamine cannot be generalized for other solvents and industrial application. Furthermore, these results showcase that specific degradation management considering solvent, capture plant and flue gas quality is reasonable. Overshooting efforts for solvent management are contra-productive and produce unnecessary waste streams, efficiency losses and costs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A machine learning framework for accurate and robust analysis of radiation detector pulses

The microscopic properties of atomic nuclei are used to study various scientific questions. They are essential for understanding the fundamental forces of nature and the chemical evolution of the universe. Detecting decay radiation from radioactive nuclei makes it possible to probe these fundamental nuclear properties. Detector waveform traces may contain additional information about the radiation. Generally, advanced signal processing techniques are needed to extract this additional information, often involving fitting the waveform with model response functions using non-linear least-squares optimization with second-order gradient methods. While this is a powerful technique, it is also computationally expensive, leading to slow processing time, which scales with the volume of data. To address this problem, we have developed a machine learning (ML) approach that infers the characteristics of traces from a model detector response function. In particular, we are interested in classifying whether a single recorded trace consists of one or two pulse constituents and estimating the pulse parameters. Furthermore, our proposed ML method can precisely extract the pulses’ parameters, such as energy and timing information, and accurately classify the pulse multiplicity of a trace. Unlike non-learning-based approaches, our ML approach uses neural networks that are significantly faster at inference, as they do not require any optimization during this stage.

Curve fitting↗
DOE OSTI2020

System code evaluation of near-term accident tolerant claddings during pressurized water reactor station blackout accidents

Following the Fukushima Daiichi nuclear accident in 2011, researches on Accident-tolerant fuels (ATFs) are currently of high interest in not only the nuclear industry but also governmental and international organizations. In this work, a quantitative evaluation of the performance of monolithic FeCrAl cladding and Cr-coated Zircaloy cladding has been performed for Pressurized Water Reactor (PWR) Station Blackout (SBO) accidents. A generic PWR model has been built in system thermal-hydraulics code TRACE based on the Surry Nuclear Power Station with counter-current natural circulation modelling capability for hotleg and steam generator U-tube components during the accidents. The base model results are then compared to MELCOR and RELAP simulations to verify the system component implementation in TRACE. Two PWR SBO scenarios were investigated, including: short-term SBO and long-term SBO with early reactor coolant pump (RCP) seal failure. These scenarios are defined to be very similar to the accidents studied in the State-of-the-Art Reactor Consequence Analysis (SOARCA) project. TRACE code is modified to reflect the oxidation kinetics of FeCrAl and Cr-coating. Larson-Miller creep rupture model is also implemented in TARCE using its built-in control systems to simulate the creep rupture of hotlegs. Additionally, the comparison between the TRACE models with and without the counter-current flow modeling resulted in significant difference when comparing ATF cladding to Zircaloy for short term SBO, while it marginal impacted the performance during long term SBO with RCP seal failure. For short term SBO, both ATF cladding underwent hot leg creep rupture ~20 min after Zircaloy cladding. While Zircaloy and Cr-coated cladding had generated significant amount of hydrogen gas (>10 kg) before the creep rupture event, FeCrAl cladding had only generated <0.5 kg of hydrogen gas. For long term SBO with RCP seal failure, significant hydrogen generation and fuel melting was predicted before hot leg creep rupture for the ATF cladding while providing only 10–20 min additional coping time compared to Zircaloy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Exceptional NH 3 Detection by Cu(cyhdc) MOF Sensor Due to H 2 O Coadsorption

Metal–organic framework (MOF)-based electrical impedance sensors are a growing class of sensors that show utility in the detection of environmentally toxic gases. Detection of trace NH 3 has been particularly difficult to design due to the low electrical response of NH 3 . However, this has been circumvented by judiciously selecting a MOF that has enhanced electrical response to NH 3 due to coadsorption with predominant atmospheric gases such as water. Herein, an MOF Cu(cyhdc) based sensor has been successfully demonstrated for the enhanced detection of environmentally toxic NH 3 gas. The sensor shows a change in impedance when it is exposed to 5 ppm of NH 3 . At 20 °C, >30% relative humidity (RH) is necessary to elicit a change, with the response increasing with RH and reaching 3170× at 92% RH, producing the largest published response to NH 3 for a MOF direct electrical sensor. In the absence of water, no change is observed toward 5 ppm of NH 3 over 20–50 °C. Here, this electrical response is largely driven by huge decreases in the imaginary component of the impedance, attributed to increased capacitance at the surface of the MOF crystallites upon NH 3 and H 2 O coadsorption. Complementary structural and microstructural characterization proves that the Cu(cyhdc) crystalline structure and morphology remain intact under trace NH 3 and/or H 2 O adsorption. Despite extremely low NH 3 , loadings seen in TGA, XPS, and FT-IR confirm NH 3 and H 2 O adsorption, and changes to the metal-carboxylate IR peak positions are observed upon NH 3 adsorption. Concentrated primarily at the outer surfaces of the MOF crystallites, this NH 3 and H 2 O coadsorption effectively increases the surface capacitance across the Cu(cyhdc) powder and enables direct electrical detection of trace NH 3 . Together, these results demonstrate how coadsorption of specific molecules (H 2 O) can be used to enable the electrical detection of trace toxic gases that would otherwise not have produced a MOF sensor response.

ammonia↗
DOE OSTI2023

Modeling the Effects of Drift Orbit Bifurcation on the Magnetopause Shadowing Loss of Radiation Belt Electrons

Abstract Last closed drift shell (LCDS) has been identified as a crucial parameter for investigating the magnetopause shadowing loss of radiation belt electrons. However, drift orbit bifurcation (DOB) effects have not been physically incorporated into the LCDS calculation. Here we calculate event‐specific LCDS using different approaches to dealing with the DOB effects, that is, tracing field lines ignoring DOB, tracing test particles rejecting field lines with DOB, and tracing particles including field lines with DOB, and then incorporate them into a radial diffusion model to simulate the fast electron dropout observed by Van Allen Probes in May 2017. The model effectively captures the fast dropout at high L* and exhibits the best agreement with data when LCDS is calculated by tracing test particles with DOB more physically included. This study represents the first quantitative modeling of the DOB effects on radiation belt magnetopause shadowing loss via a more physical specification of LCDS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

A critical look at the prediction of the temperature field around a laser-induced melt pool on metallic substrates

The study of microstructure evolution in additive manufacturing of metals would be aided by knowing the thermal history. Since temperature measurements beneath the surface are difficult, estimates are obtained from computational thermo-mechanical models calibrated against traces left in the sample revealed after etching, such as the trace of the melt pool boundary. Here we examine the question of how reliable thermal histories computed from a model that reproduces the melt pool trace are. To this end, we perform experiments in which one of two different laser beams moves with constant velocity and power over a substrate of 17-4PH SS or Ti-6Al-4V, with low enough power to avoid generating a keyhole. We find that thermal histories appear to be reliably computed provided that (a) the power density distribution of the laser beam over the substrate is well characterized, and (b) convective heat transport effects are accounted for. Poor control of the laser beam leads to potentially multiple three-dimensional melt pool shapes compatible with the melt pool trace, and therefore to multiple potential thermal histories. Ignoring convective effects leads to results that are inconsistent with experiments, even for the mild melt pools here.

42 ENGINEERING↗
DOE OSTI2022

Cross-correlation of Dark Energy Survey Year 3 lensing data with ACT and P l a n c k thermal Sunyaev-Zel’dovich effect observations. II. Modeling and constraints on halo pressure profiles

Hot, ionized gas leaves an imprint on the cosmic microwave background via the thermal Sunyaev-Zel’dovich (tSZ) effect. The cross-correlation of gravitational lensing (which traces the projected mass) with the tSZ effect (which traces the projected gas pressure) is a powerful probe of the thermal state of ionized baryons throughout the Universe and is sensitive to effects such as baryonic feedback. In a companion paper (Gatti et al. Phys. Rev. D 105, 123525 (2022)), we present tomographic measurements and validation tests of the cross-correlation between Galaxy shear measurements from the first three years of observations of the Dark Energy Survey and tSZ measurements from a combination of Atacama Cosmology Telescope and Planck observations. In this work, we use the same measurements to constrain models for the pressure profiles of halos across a wide range of halo mass and redshift. We find evidence for reduced pressure in low-mass halos, consistent with predictions for the effects of feedback from active Galactic nuclei. We infer the hydrostatic mass bias (B ≡ M 500c /M SZ from our measurements, finding B = 1.8 ± 0.1 when adopting the Planck-preferred cosmological parameters. We additionally find that our measurements are consistent with a nonzero redshift evolution of B, with the correct sign and sufficient magnitude to explain the mass bias necessary to reconcile cluster count measurements with the Planck-preferred cosmology. Our analysis introduces a model for the impact of intrinsic alignments (IAs) of galaxy shapes on the shear-tSZ correlation. We show that IA can have a significant impact on these correlations at current noise levels.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

I/O Bottleneck Detection and Tuning: Connecting the Dots using Interactive Log Analysis

Using parallel file systems efficiently is a tricky problem due to inter-dependencies among multiple layers of I/O software, including high-level I/O libraries (HDF5, netCDF, etc.), MPI-IO, POSIX, and file systems (GPFS, Lustre, etc.). Profiling tools such as Darshan collect traces to help understand the I/O performance behavior. However, there are significant gaps in analyzing the collected traces and then applying tuning options offered by various layers of I/O software. Seeking to connect the dots between I/O bottleneck detection and tuning, we propose DXT Explorer, an interactive log analysis tool. In this paper, we present a case study using our interactive log analysis tool to identify and apply various I/O optimizations. We report an evaluation of performance improvement achieved for four I/O kernels extracted from science applications.

Bez, Jean Luca↗
DOE OSTI2022

pnnl/memgaze

MemGaze is a memory analysis toolset that combines high-resolution trace analysis and low overhead measurement, both with respect to time and space. It provides high-resolution by collecting world-level memory access traces, where the highest resolution supported is back-to-back sequences. It achieves low-overhead in space and time by leveraging sampling and various methods of hardware support for collecting traces. Its post-mortem trace processing provides multiresolution analysis for locations vs. operations; accesses vs. spatio-temporal reuse, and reuse (distance, rate, volume) vs. access patterns.

Central, PNNL Developer↗
DOE OSTI2024

Proteomics Analysis of Human Contaminant Proteins

Complete characterization of unknowns via proteomics remains challenging. There exist regions of mass spectrometry-based proteomics data where empirical measurements are not attributed to peptides, and/or sequenced peptides from mass spectra are not attributed to any source. These uncharacterized regions are known as the “dark” proteome. Many proteomics tools rely on some a priori knowledge of sample composition; few tools allow for investigation of unknowns without relying on composition assumptions. Further, the potential low abundance of minor traces in these uncharacterized regions can make elucidation of the “dark” proteome challenging. Herein, we describe the development and evaluation of approaches to study the “dark” proteome and move towards an untargeted approach for more complete characterization, namely by studying minor human protein traces in non-human samples and combining that approach with non-human source organism identification without relying on assumptions. Human protein markers, in the form of genetically variant peptides, have been extensively examined in a variety of human matrices, including blood, plasma, and hair, but have yet to be investigated in non-human samples, such as cell cultures, as human contaminant traces. Genetically variant peptides are those that are found in proteins carrying single nucleotide polymorphisms. In this work, we aimed to (1) investigate the feasibility of detecting human contaminant genetically variant peptides (GVPs) in a diverse set of non-human organisms using public proteomics data and a computational pipeline, as well as to (2) develop a combined capability for untargeted source organism characterization and GVP detection. To our knowledge, this is the first report of applying these approaches towards a more complete proteomic characterization of unknowns. We successfully demonstrate the feasibility of broad human contaminant GVP detection in proteomics data, develop a better understanding of GVP detectability, characterize the sample-to-sample variability in GVP detection, and identify a core set of GVPs that can potentially be used as markers indicative of the human contaminant traces portion of the “dark” proteome. Further, we developed and evaluated a combined pipeline, MARLOWE-GVP, that enables both untargeted source organism characterization and GVP detection. We show high accuracy of correct source organism characterization and high degree of similarity of human contaminant GVP detection compared to the conventional approach. Success on both these efforts have allowed us to advance our understanding and characterization of the “dark” proteome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Addressing Low-Cost Methane Sensor Calibration Shortcomings with Machine Learning

Quantifying methane emissions is essential for meeting near-term climate goals and is typically carried out using methane concentrations measured downwind of the source. One major source of methane that is important to observe and promptly remediate is fugitive emissions from oil and gas production sites but installing methane sensors at the thousands of sites within a production basin is expensive. In recent years, relatively inexpensive metal oxide sensors have been used to measure methane concentrations at production sites. Current methods used to calibrate metal oxide sensors have been shown to have significant shortcomings, resulting in limited confidence in methane concentrations generated by these sensors. To address this, we investigate using machine learning (ML) to generate a model that converts metal oxide sensor output to methane mixing ratios. To generate test data, two metal oxide sensors, TGS2600 and TGS2611, were collocated with a trace methane analyzer downwind of controlled methane releases. Over the duration of the measurements, the trace gas analyzer’s average methane mixing ratio was 2.40 ppm with a maximum of 147.6 ppm. The average calculated methane mixing ratios for the TGS2600 and TGS2611 using the ML algorithm were 2.42 ppm and 2.40 ppm, with maximum values of 117.5 ppm and 106.3 ppm, respectively. A comparison of histograms generated using the analyzer and metal oxide sensors mixing ratios shows overlap coefficients of 0.95 and 0.94 for the TGS2600 and TGS2611, respectively. Overall, our results showed there was a good agreement between the ML-derived metal oxide sensors’ mixing ratios and those generated using the more accurate trace gas analyzer. This suggests that the response of lower-cost sensors calibrated using ML could be used to generate mixing ratios with precision and accuracy comparable to higher priced trace methane analyzers. This would improve confidence in low-cost sensors’ response, reduce the cost of sensor deployment, and allow for timely and accurate tracking of methane emissions.

03 NATURAL GAS↗
DOE OSTI2020

Software classification using phylogenetic techniques

Software, such as malware, may be classified using phylogenetic techniques. An evolutionary history of a representative set of software programs may be reconstructed to generate a reference phylogeny. Dynamic traces of the representative software programs may be obtained. The dynamic traces may include time-ordered sequences of execution commands extracted from running software binaries. Metrics may be developed using the dynamic traces. One or more unknown software programs may then be classified against the reference phylogeny using the metrics developed using the dynamic traces of the representative set of software programs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Circuit board and method of forming same

A circuit board comprising a substrate and a circuit trace. The substrate includes a surface etched via ion milling over a circuit area such that the surface has an increased roughness. The circuit trace forms portions of an electronic circuit and may be created from a thin conductive film deposited on the surface within the circuit area. The circuit trace adheres more strongly to the roughened substrate surface, which prevents the circuit trace from peeling or becoming delaminated from the substrate surface.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Damage Evolution of Double-Sided Copper Conductor on Multi-layer Flexible Substrate Under Bending

Abstract—Thin-film conductors continue to play an important role in flexible electronics, and thus, the performance and reliability of such conductors under mechanical loading such as stretch, bend, and twist need to be studied through experiments as well as simulations. This paper focuses on the damage evolution of the thin-film conductors under cyclic bending. Four types of double-sided copper conductors: straight trace without coverlay, straight trace with coverlay, notched trace without coverlay, and notched trace with coverlay on multi-layer substrates were studied in this work. The adaptive curvature flexure test method, which is suitable for thin-film bending, was employed in this work. Adaptive curvature flexure test is one where the flexible substrate with its conductor is positioned between two parallel plates, and the parallel plates are moved relative to each other such that the gap distance between the parallel plates changes in one of the configurations of the adaptive curvature flexure test. Different strain levels can be achieved easily in such an adaptive curvature flexure test by controlling the gap distance between the parallel plates. By subjecting flexible substrates with thin conductors to such bend tests, the fatigue life of the specimen was determined for different magnitudes of strain ranges. The results were then compared among the four types of conductors. Specimens were designed such that the conductors were placed on both sides of the substrate so that the one of the conductors would undergo tensile straining, while the other one would undergo compressive straining. It was shown that the fatigue life was highly dependent on the magnitude of strain range, and that the conductor on the compressive side failed sooner than that on the tensile side. The failed specimens were examined in a microscope at different number of cycles. Also, the resistance of the conductors, which is directly related to the reliability of thin-film conductors, was monitored in-situ during bending. The resistance change with the strain range change as well as the resistance progression with the number of cycles in tensile as well as compressive mode were determined, and such information is then used to create failure prediction models for thin-film conductors on flexible substrates.

damage evolution, flexible conductor, multi-layer ↗
DOE OSTI2022

Locating underground features with seismic data processing

Methods are presented for determining the location of underground features (e.g., CO 2 ). One method includes capturing, by sensors distributed throughout a region, seismic traces associated with seismic signals generated by a seismic source. For multiple sensors, active noise is identified or passive noise is measured within each seismic trace and values for attributes associated with the active or passive noise are determined. Further, an unsupervised machine-learning model, based on the values of the attributes, is utilized to determine noise characteristics for multiple sensors. The sensors are grouped in clusters based on the noise characteristics for each sensor. For multiple clusters, a noise filter is created based on the noise characteristics of the sensors in the cluster, and the noise filter of the cluster is applied, for multiple sensors, to the seismic traces of the sensor. Additionally, the filtered seismic traces are analyzed to determine a location of CO 2 underground.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

High resolution, high conductivity components by aerosol jet printing

Highly conductive electrical traces formed over mechanical steps or on non-planar surfaces with linewidths of 10 to 100 μm and a method for forming such electrical traces are disclosed. The method employs two steps, with the first step using an aerosol jet printing (AJP) process to form thin electrical traces that serve as the seed layers for the second step. The first step preferably employs multiple passes with the AJP to create multiple seed sub-layers with improved continuity and conductivity. In the second step, the seed layers are subjected to an electrodeposition process that forms the bulk of the thickness of the electrical traces. The electrodeposition process may include one, two, or three phases at corresponding low or high biases, with low biases providing denser, more highly conductive plating sub-layers, while high biases provide plating sub-layers having better gap bridging properties.

Lavin, Judith Maria↗