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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Understanding Irrigation Impacts on Low-Level Jets over the Great Plains

Low-level jets (LLJs) over the Great Plains are well-known for their importance in transporting moisture from the Gulf of Mexico and forming precipitation in the Central US. However, the impact of irrigation practice on LLJs is rarely studied. To understand the irrigation impact on the Great Plains LLJs, the Weather Research and Forecasting (WRF) model is employed with and without an irrigation scheme. The simulated wind field is evaluated against the observed wind from Midlatitude Continental Convective Clouds Experiment (MC3E). The results show that adding irrigation improves the simulated wind, especially at lower altitudes below 800 hPa. Irrigation reduces the LLJ frequency over the Great Plains, mainly by reducing the intense LLJ frequency. The reduced LLJ frequency is caused by the irrigation-induced weakening of meridional wind. The favorable conditions for LLJs have been identified by examining the mechanism associated with LLJs: a ridge-like pattern with weak and calm synoptic-scale conditions in the mid-levels and a strong west-east temperature gradient at lower levels that promote meridional winds. Irrigation-induced cooling leads to a baroclinic pattern with high pressure at lower altitudes over the irrigation region and low pressure in the mid- and upper levels in the downstream region, resulting in a northerly component that hinders the formation of LLJs. Low-level surface cooling also decreases the west-east temperature gradient and hence weakens the thermal wind forcing. The irrigation-induced mid-level low and weaker west-east temperature gradient are responsible for the reduced meridional winds and the reduced LLJ frequencies.

Yang, Zhao↗
DOE OSTI2023

Understanding the diversity of the West African monsoon system change projected by CORDEX-CORE regional climate models

Understanding real uncertainties in projections is needed to support actions of decision and policy makers. In this study, two state-of-the-art regional climate models with ~ 25 km horizontal resolution forced with three different global climate models are employed to investigate the response of the West African Monsoon (WAM) system under the low (RCP2.6) and high (RCP8.5) emission scenarios. We make a step towards assessing the plausibility of rainfall change (ΔPr) patterns based on the models’ ability to realistically represent the WAM system under the historical period, and by analyzing changes in mechanisms associated with ΔPr patterns. Under global warming, experiments exhibit diverse ΔPr patterns underpinned by different combinations of mechanisms operating simultaneously. A dipole-like surface pressure change between the Sahara Desert and the Guinea Coast appears to be a differentiating factor between experiments featuring homogeneous or increased rainfall over all or a part of the Sahel from those simulating heterogeneous or reduced rainfall over the same domain. This dipole acts by modulating the amount and the extent of deepening of the monsoon flux inland, and hence the latitudinal positioning of the monsoon convective system. This process contributes to moistening the whole or central and eastern Sahel in some experiments while drying the Guinea Coast. The West African Westerly Jet (WAWJ) is responsible for strengthening and moistening the western Sahel under RCP2.6. However, the WAMJ becomes much stronger under RCP8.5 and may have contributed to the drying of the western Sahel by shifting moisture eastwards in addition to the mid-tropospheric moisture divergence through enhanced African Easterly Jet. Furthermore, for experiments expecting wetting (drying) of the Sahel, the strengthening (weakening) of the tropical easterly jet may have contributed to the projected intensification (reduction) of WAM rainfall by favoring uplift (downlift) above 600 hPa. It also emerges that the ΔPr patterns from REMO2015 experiments are likely more plausible than those from RegCM4-v7. The impacts of strong warming on the regional hydrological cycle are further investigated and we found that changes gradually intensify with the level of radiative forcing, highlighting the importance of mitigating warming as recommended by the Paris agreement.

CORDEX-CORE↗
DOE OSTI2018

Understanding Clinical Mammographic Breast Density Assessment: a Deep Learning Perspective

Mammographic breast density has been established as an independent risk marker for developing breast cancer. Breast density assessment is a routine clinical need in breast cancer screening and current standard is using the Breast Imaging and Reporting Data System (BI-RADS) criteria including four qualitative categories (i.e., fatty, scattered density, heterogeneously dense, or extremely dense). In each mammogram examination, a breast is typically imaged with two different views, i.e., the mediolateral oblique (MLO) view and cranial caudal (CC) view. The BI-RADS-based breast density assessment is a qualitative process made by visual observation of both the MLO and CC views by radiologists, where there is a notable inter- and intra-reader variability. In order to maintain consistency and accuracy in BI-RADS-based breast density assessment, gaining understanding on radiologists’ reading behaviors will be educational. In this study, we proposed to leverage the newly emerged deep learning approach to investigate how the MLO and CC view images of a mammogram examination may have been clinically used by radiologists in coming up with a BI-RADS density category. We implemented a convolutional neural network (CNN)-based deep learning model, aimed at distinguishing the breast density categories using a large (15,415 images) set of real-world clinical mammogram images. Our results showed that the classification of density categories (in terms of area under the receiver operating characteristic curve) using MLO view images is significantly higher than that using the CC view. This indicates that most likely it is the MLO view that the radiologists have predominately used to determine the breast density BI-RADS categories. Our study holds a potential to further interpret radiologists’ reading characteristics, enhance personalized clinical training to radiologists, and ultimately reduce reader variations in breast density assessment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Accretion disks, quasars and cosmology: meandering towards understanding

Abstract As Setti and Woltjer noted back in 1973, one can use quasars to construct the Hubble diagram; however, the actual application of the idea was not that straightforward. It took years to implement the proposition successfully. Most ways to employ quasars for cosmology now require an advanced understanding of their structure, step by step. We briefly review this progress, with unavoidable personal biases, and concentrate on bright unobscured sources. We will mention the problem of the gas flow character close to the innermost stable circular orbit near the black hole, as discussed five decades ago. This problem later led to the development of the slim disk scenario and is recently revived in the context of Magnetically Arrested Disks (MAD) and Standard and Normal Evolution (SANE) models. We also discuss the hot or warm corona issue, which is still under debate and complicates the analysis of X-ray reflection. We present the scenario of the formation of the low ionization part of the Broad Line Region as a failed wind powered by radiation pressure acting on dust (Failed Radiatively Driven Dusty Outflow – FRADO). Next, we examine the cosmological constraints currently achievable with quasars, primarily concentrating on light echo methods (continuum time delays and spectral-line time delays to the continuum) that are (or should be) incorporating the progress mentioned above. Finally, we briefly discuss prospects in this lively subject area.

Astronomy & Astrophysics↗
DOE OSTI2024

Understanding the Impact of Fuel on Surfactant Microstructure of Firefighting Foam

Abstract Aqueous film-forming foam is being phased out due to the environmental impacts of fluorinated surfactants contained in the firefighting foams. To develop an environmentally friendly firefighting foam, it is important to understand the factors controlling the firefighting performance of surfactants. Fuel transport through foam has been considered as a dominant mechanism for foam collapse. Therefore, the impact of fuels (heptane, octane and trimethylbenzene (TMB)) on surfactant microstructure was studied for three different types of surfactants (Capstone, Glucopon, and siloxane) that have applications in firefighting foam. Multiple techniques were used to identify the microstructure and interfacial properties of surfactants with and without exposure to liquid fuel. The ignition time of fuel vapor through foam and solubility of fuel through liquid surfactant solution were measured as well. This work shows fuel solubility has an impact on the surfactant microstructure and interfacial properties. In addition, fuel solubility and vapor pressure affect the ignition time of fuel vapors.

Engineering↗
DOE OSTI2018

Understanding and quantifying the systematic effects of clutter within a radiation detection scene

Because of low signal-to-noise ratios, the main difficultly in real-world detection scenarios is distinguishing between benign sources and potentially-threatening radioactive materials. The variability in observed signal during a radiation detection search operation can be contributed to the stochastic nature of the underlying physics and the systematic errors inherent to the detection systems employed. This variability is compounded for dynamic detection scenarios, where objects, referred to as clutter, traverse through the primary detection scene, introducing potential suppressions in the observed signal due to the attenuation of background radiation. This study examines the impact that clutter, namely automobiles such as small utility vehicles, sedans, and trucks, produces on the observed signal in a 2 in. × 4 in. × 16 in. NaI(Tl) detector. The clutter is identified and tracked in the detection scene using a time-synced video camera and a 2-D light distance and ranging contextual sensors. Two experiments were performed on the Oak Ridge National Laboratory reservation: one using a distributed source within the scene to understand the systematics of detecting and analyzing the clutter, and the second experiment mimicking an urban environment with large buildings positioned on either side of a roadway. The experiments exhibited unique results in the amount of signal suppression and variability of the cluttered signal, both demonstrating an observable suppression from the clutter-free background. These results reveal a new potential category of signal noise intrinsic to real-world detection scenarios that should be considered when establishing detection thresholds based on expected values.

Stewart, Ian R.↗
DOE OSTI2020

What matters the most? Understanding individual tornado preparedness using machine learning

Scholars from various disciplines have long attempted to identify the variables most closely associated with individual preparedness. Therefore, we now have much more knowledge regarding these factors and their association with individual preparedness behaviors. However, it has not been sufficiently discussed how decisive many of these factors are in encouraging preparedness. In this article, we seek to examine what factors, among the many examined in previous studies, are most central to engendering emergency preparedness in individuals particularly for tornadoes by utilizing a relatively uncommon machine learning technique in disaster management literature. Using unique survey data, we find that in the case of tornado preparedness the most decisive variables are related to personal experiences and economic circumstances rather than basic demographics. Our findings contribute to scholarly endeavors to understand and promote individual tornado preparedness behaviors by highlighting the variables most likely to shape tornado preparedness at an individual level.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Understanding Microstructural Evolution During Rapid Heat Treatment of Microalloyed Steels Through Computational Modeling, Advanced Physical Simulation, and Multiscale Characterization Techniques

An AISI 1045 steel modified with vanadium (V) and niobium (Nb) was studied to evaluate microstructural conditioning prior to and throughout a rapid heat treat process. In order to accomplish this, both computational and physical simulation techniques have been employed with the goal of assessing the microstructural evolution in a medium-carbon bar steel during the rapid austenitization and quenching procedures involved in an induction hardening process. The appropriate thermal profiles for induction hardening were obtained through finite element modeling using Flux 2D software. Physical simulations of the induction hardening process were carried out using a Gleeble{sup ®} 3500. Analysis of prior austenite grain size is complemented by observation of nanoscale carbonitride precipitation via transmission electron microscopy, scanning transmission electron microscopy, and high-energy synchrotron small-angle x-ray scattering. Through a combination of characterization techniques, this study presents a deeper understanding of nano- and microstructural changes occurring in a microalloyed steel during an induction hardening process.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Understanding of the Elemental Diffusion Behavior in Concentrated Solid Solution Alloys

As one of the core effects on the high-temperature structural stability, the so-called “sluggish diffusion effect” in high-entropy alloy (HEA) has attracted much attention. Experimental investigations on the diffusion kinetics have been carried out in a few HEA systems, such as Al-Co-Cr-Fe-Ni and Co-Cr-Fe-Mn-Ni. However, the mechanisms behind this effect remain unclear. To better understand the diffusion kinetics of the HEAs, a combined computational/experimental approach is employed in the current study. In the present work, a self-consistent atomic mobility database is developed for the face-centered cubic (fcc) phase of the Co-Cr-Fe-Mn-Ni quinary system. The simulated diffusion coefficients and concentration profiles using this database can well describe the experimental data both from this work and the literatures. The validated mobility database is then used to calculate the tracer diffusion coefficients of Ni in the subsystems of the Co-Cr-Fe-Mn-Ni system with equiatomic ratios. The comparisons of these calculated diffusion coefficients reveal that the diffusion of Ni is not inevitably more sluggish with increasing number of components in the subsystem even with homologous temperature. Taking advantage of computational thermodynamics, the diffusivities of alloying elements with composition and/or temperature are also calculated. Furthermore, these calculations provide us an overall picture of the diffusion kinetics within the Co-Cr-Fe-Mn-Ni system.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Cardio-oncology: Understanding cardiotoxicity to guide patient focused imaging

Current cancer therapy has led to tremendous improvements in outcomes. These therapies rely both on established therapies, such as anthracyclines and radiation, and molecularly-targeted therapies, such as tyrosine kinase inhibitors and immune modulators. Integrative care for patients with cancer must consider the potential effects of these therapies on a variety of organ systems, including the cardiovascular system. As a result, specialties such as cardio-oncology have developed to identify these effects, determine how to best monitor for these effects, and how to treat and ultimately prevent these effects while allowing the patient to receive the therapy they require for their cancer. This review provides a basis for understanding the cardiovascular effects of cancer therapies so that the most appropriate imaging modality may be selected to prevent and treat these effects.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Understanding poromechanical response of a biogenic coalbed methane reservoir

Abstract Biogenic coalbed methane (BCBM) reservoirs aim to produce methane from in situ coal deposits following microbial conversion of coal. Success of BCBM reservoirs requires economic methane production within an acceptable timeframe. The work reported here quantifies the findings of previously published qualitative work, where it was found that bioconversion induces strains in the pore, matrix and bulk scales. Using imaging and dynamic strain monitoring techniques, the bioconversion induced strain is quantified here. To understand the effect of these strains from a reservoir geomechanics perspective, a corresponding poromechanical model is developed. Furthermore, findings of imaging experiments are validated using core-flooding flow experiments. Finally, expected field-scale behavior of the permeability response of a BCBM operation is modeled and analyzed. The results of the study indicated that, for Illinois coals, bioconversion induced strains result in a decrease in fracture porosity, resulting in a detrimental permeability drop in excess of 60% during bioconversion, which festers itself exponentially throughout its producing life. Results indicate that reservoirs with high initial permeability that will support higher Darcian flowrates, would be better suited for coal bioconversion, thereby providing a site-selection criteria for BCBM operations.

Pandey, Rohit (ORCID:0009000415483436)↗
DOE OSTI2020

Understanding Calibration and Error Propagation in Longitudinal and Lateral Manganin Gauge Shock Experiments

Soda-lime glass remains elastic under shock pressures up to approximately 6.5 GPa. In this paper, soda lime glass shock experiments are used to understand the calibration and error propagation in longitudinal and lateral manganin gauge experiments. The errors in the calibration process for both longitudinal and lateral manganin gauge experiments are identified and discussed. Five soda-lime glass experiments up to 3 GPa are analyzed using this refined technique. The results show good agreement between the experimental data and the published calibration by Rosenberg and Moshel. Errors are propagated from the experimental data measurements and the assumptions that are made in the calibration, where the bulk of the error seems to come from uncertainty in the dynamic yield strength of manganin. Finally, the method presented in this paper allows for analysis of dynamic shock experiments with longitudinal and lateral manganin gauges including error propagation.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Chapter 7 - Simulations of Arctic Mixed-Phase Boundary Layer Clouds: Advances in Understanding and Outstanding Questions. In: Mixed-Phase Clouds, Observations and Modeling

An overview of mixed-phase boundary layer cloud simulations emphasizes what detailed studies reveal about the level of understanding of microphysical processes, using analogous liquid-phase boundary layer clouds as a reference for the dynamical conditions. We focus primarily on modeling results from three major field campaign case studies, spanning a range of liquid water path, aerosol loading, cloud temperatures, and active processes (including drizzle, aggregation, and riming). Simulations with detailed microphysics are able to reproduce basic aspects of all three case studies, including continuous ice formation within the context of a well-mixed liquid-cloud-topped layer. However, simulations constrained with measurements of ice nuclei generally underpredict the observed amount of ice present, indicating a possible role for ice multiplication that is poorly established. Assumed ice properties may also bear a significant influence on the water vapor budget and reflectivity properties, but remain imprecisely quantified on a case study basis.

Arctic clouds↗
DOE OSTI2017

Understanding the Performance of Automotive Catalysts via Spatial Resolution of Reactions inside Honeycomb Monoliths

By directly resolving spatial and temporal species distributions within operating honeycomb monolith catalysts, spatially resolved capillary inlet mass spectrometry (SpaciMS) provides a uniquely enabling perspective for advancing automotive catalysis. Specifically, the ability to follow the spatiotemporal evolution of reactions throughout the catalyst is a significant advantage over inlet-and-effluent-limited analysis. Intracatalyst resolution elucidates numerous catalyst details including the network and sequence of reactions, clarifying reaction pathways; the relative rates of different reactions and impacts of operating conditions and catalyst state; and reaction dynamics and intermediate species that exist only within the catalyst. These details provide a better understanding of how the catalyst functions and have basic and practical benefits; e.g., catalyst system design; strategies for on-road catalyst state assessment, control, and on-board diagnostics; and creating robust and accurate predictive catalyst models. Moreover, such spatiotemporally distributed data provide for critical model assessment, and identification of improvement opportunities that might not be apparent from effluent assessment; i.e., while an incorrectly formulated model may provide correct effluent predictions, one that can accurately predict the spatiotemporal evolution of reactions along the catalyst channels will be more robust, accurate, and reliable. In such ways, intracatalyst diagnostics comprehensively enable improved design and development tools, and faster and lower-cost development of more efficient and durable automotive catalyst systems. Beyond these direct contributions, SpaciMS has spawned and been applied to enable other analytical techniques for resolving transient distributed intracatalyst performance. This chapter focuses on SpaciMS applications and associated catalyst insights and improvements, with specific sections related to lean NOx traps, selective catalytic reduction catalysts, oxidation catalysts, and particulate filters. The objective is to promote broader use and development of intracatalyst analytical methods, and thereby expand the insights resulting from this detailed perspective for advancing automotive catalyst technologies.

Partridge Jr, William↗
DOE OSTI2020

Understanding the Effects of Vehicle Platoons on Crash Type and Severity

Crash type is an informative indicator to infer driving behaviors and conditions that cause a crash. For example, rear-end and side-swipe crashes are typically caused by improper vehicle interaction such as sudden lane-changing or speed control while hit-object crashes are likely the result of a single driver’s mistake. This study investigated the impact of vehicles travelling as a group (platoon) and its configuration (i.e., types of vehicles consisting of the platoon) on crash type and severity since the vehicles could affect each other when travelling in close proximity. This study applied Generalized Structure Equation Modeling (GSEM) to capture the complex relationships among the various crash factors such as traffic condition, driver characteristics, environmental conditions, and vehicle interaction to the crash attributes including type and severity. This study collected over 3 million individual vehicle data from 39 traffic count sites in California to estimate the vehicle interactions and driving behaviors. The microscopic traffic data are matched to 1417 crash reports. Results showed that vehicles traveling in platoons are associated with more rear-end and side-swipe crashes. Speed difference in the platoon had a positive effect on hit-object crashes if the platoon comprises vehicles of homogeneous type – either trucks or non-trucks. In addition, human factors such as age and gender were identified as significant influential factors in all type of crashes, however truck involvement particularly played an important role amongst side-swipe crashes. Crash severity was negatively affected by total flow, and rear-end crashes were more likely to be severe compared with hit-object crashes. Based on findings, this study suggests practical operational strategies to reduce traffic instability associated with platooned vehicle patterns. Understanding the high-risk factors for different crash types and severities would provide valuable insights for decision-makers and transportation engineers to develop targeted intervention strategies in consideration of road users and traffic conditions such as fleet mix and speed.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Understanding and quantifying electron beam effects during in situ TEM nanomechanical tensile testing on metal thin films

Transmission electron microscopy (TEM) imaging relies on high energy electrons for atomic scale resolution, however, the electrons themselves interact with and may alter the material being imaged. Using an in situ TEM MEMS-based nanomechanical testing technique, the effect of the electron beam (e-beam) on the deformation behavior of nanocrystalline Al and ultrafine-grained Au is investigated and quantified. We show that the e-beam enhances plastic deformation, leading to an increase in plastic strain rate and a decrease in true activation volume V* in Al (28 to 21b 3 , with b being the Burgers vector length). The e-beam has a much weaker effect on Au. The e-beam effect is not caused by knock-on damage, but rather an effective temperature increase due to additional atomic fluctuations provided by the e-beam. The effective temperature increase is larger for Al than Au. This e-beam effect does not change the deformation mechanisms, but instead accelerates the stress-driven, thermally activated plastic deformation. These experiments provide insight into the effects of the e-beam on plastic deformation in different metals and underscore the importance of understanding and quantifying these effects for proper interpretation of measured mechanical properties during in situ TEM experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Understanding interactions between biomolecules and two-dimensional nanomaterials using in silico microscopes

We report two-dimensional (2D) nanomaterials such as graphene are increasingly used in research and industry for various biomedical applications. Extensive experimental and theoretical studies have revealed that 2D nanomaterials are promising drug delivery vehicles, yet certain materials exhibit toxicity under biological conditions. So far, it is known that 2D nanomaterials possess strong adsorption propensities for biomolecules. To mitigate potential toxicity and retain favorable physical and chemical properties of 2D nanomaterials, it is necessary to explore the underlying mechanisms of interactions between biomolecules and nanomaterials for the subsequent design of biocompatible 2D nanomaterials for nanomedicine. The purpose of this review is to integrate experimental findings with theoretical observations and facilitate the study of 2D nanomaterial interaction with biomolecules at the molecular level. We discuss the current understanding and progress of 2D nanomaterial interaction with proteins, lipid membranes, and DNA based on molecular dynamics (MD) simulation. In this review, we focus on the 2D graphene nanosheet and briefly discuss other 2D nanomaterials. With the ever-growing computing power, we can image nanoscale processes using MD simulation that are otherwise not observable in experiment. We expect that molecular characterization of the complex behavior between 2D nanomaterials and biomolecules will help fulfill the goal of designing effective 2D nanomaterials as drug delivery platforms.

2D nanomaterials↗
DOE OSTI2021

Mapping the Path Forward to Next Generation Algal Technologies: Workshop on Understanding the Rules of Life and Complexity in Algal Systems

Algal technology offers enormous potential as a source of renewable biomass and bioproducts for fuels, biochemicals, nutrients, and numerous other applications. While tremendous opportunities exist, significant challenges are also present in harnessing and utilizing this valuable and potentially sustainable bioproduction platform. Funded by a joint partnership between the Bioenergy Technologies Office (BETO) at the Department of Energy (DOE) and the National Science Foundation (NSF), the recent virtual workshop, "Understanding the Rules of Life: Complexity in Algal Systems Workshop," was organized to bring together thought leaders from academia, national laboratories and other government agencies, and industry to identify key challenges and propose research strategies to overcome these barriers. Two parallel sessions were undertaken: 1) algae strain and toolkit development and 2) algal ecosystem and microbiome dynamics, in order to advance algae engineering and cultivation efforts. In each session, attendees discussed the most pressing challenges from the perspective of model systems and omics analysis. Themes such as genetic engineering toolboxes, translation from the laboratory to outdoor cultivation, functional genomics, metabolomics, algal ecology, consortial design, microbiome dynamics, mathematical models, and data analytics emerged from the discussion. Overall, this workshop has served to elucidate the key hurdles and many opportunities present as we continue to advance algal science and technology from the laboratory and into the commercial realm.

09 BIOMASS FUELS↗