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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 271 records · Page 15

Cradle-to-Grave Lifecycle Analysis of U.S. Medium- and Heavy-Duty Vehicle-Fuel Pathways: A Greenhouse Gas Emissions Assessment of Current (2021) and Future (2035) Technologies

This study presents a cradle-to-grave lifecycle analysis of energy use and greenhouse gas (GHG) emissions for U.S. medium- and heavy-duty vehicles across current (2021) and future (2035) technologies using the Greenhouse gas, Regulated Emissions, and Energy use in Technologies (GREET) model with industry-vetted assumptions. Results vary across vehicle classes but point to common trends: today, battery electric vehicles (BEVs) offer significant (10–60%) GHG emissions reduction compared to diesel internal combustion engine vehicles and are the lowest emissions option per ton-mile of cargo movement, followed by hydrogen fuel cell electric vehicles (FCEVs) (5–50% emissions reduction). Emissions savings depend largely on the duty cycle and fuel economy of the vehicle type. Future vehicle technology advancements result in comparable emission reductions associated with BEVs and hydrogen FCEVs. Weight-limited BEV trucks see less per-ton-mile emissions reduction due to the impact of battery weight on increased vehicle weight and reduced payload capacity. By 2035, improvements in vehicle efficiency can reduce emissions across all powertrains. However, very low levels of emissions require switching vehicles’ use-phase fuel/energy to low-carbon fuels and electricity. Renewable diesel, e-fuels, hydrogen produced from natural gas with carbon capture and storage or renewables, and use of low-carbon electricity can all achieve over 70% reduction in GHG emissions from the current day diesel-based internal combustion engine vehicle.

alternative fuels↗

Automatic Drift Correction through Nonlinear Sensing

For successful design and operation of advanced monitoring and control systems, engineers rely on high quality sensor signals that are simultaneously accurate, representative, voluminous, and timely. Unfortunately, sensor faults are common and lead to short-lived symptoms, such as outliers and spikes as well as long-lived symptoms, such as sensor drift. Sensor drift belongs to the category of incipient faults. These are particularly challenging to detect, diagnose, and correct as the time scales of these faults are typically longer than the time scales of the system dynamics that are of interest. Moreover, if sensor drift occurs as a result of exposure to measured medium, then it is likely that multiple sensors will exhibit similar drift rates, thus challenging fault management strategies based on redundancy. In this contribution, we present a first method that can handle this unique challenge.

Chowdhury, Dhruba↗

Current state and future trends in boundary layer control on lifting surfaces

Successful flow control may bring numerous benefits, such as flow stabilization, flow reattachment, separation delay, drag reduction, lift increase, aerodynamic performance improvement, energy efficiency increase, shock delay or weakening, noise reduction, etc. For these purposes, many different flow control devices, which can be classified as passive, semi-active and active, have been designed and tested. This review paper aims to highlight the most promising and commonly employed boundary layer control methods as well as outline their potential in specific applications in aerospace and energy engineering. Referenced studies, performed on various geometries (flat plates, channels, airfoils, wings, blades, cylinders), are primarily numerical or experimental. Although enhanced aerodynamic performance is achieved in many cases, further research is required to draw general conclusions. This paper aims to demonstrate that, in the future, we may expect further developments of flow control actuators, as well as their increased application.

42 ENGINEERING↗

Dispersion-Engineered Deep Sub-Wavelength Plasmonic Metasurfaces for Broadband Seira Applications

Surface enhanced infrared absorption (SEIRA) spectroscopy is a powerful tool in which plasmonically enhanced electromagnetic fields provide high-sensitivity molecular detection. Most SEIRA platforms operate at a single resonant frequency, which must be tuned to match that of the target molecule, and commonly rely on time-consuming lithographic techniques. This study presents a high-throughput and cost-effective plasmonic metasurface for broadband, tunable, and strong infrared signal enhancement. The platform is built upon the principle of dispersion-engineered plasmonic Fabry–Pérot (FP) nanocavity arrays. It offers 1) tight squeezing of infrared (IR) photons into deep sub-wavelength nano-volumes and 2) spectrally tunable near-field enhancements of up to ≈10 6 , two to three orders of magnitude higher than most optical metasurface systems. By coupling multilayer nano-thin film deposition and nanoskiving fabrication techniques, the dispersive FP metasurfaces can be rapidly and reproducibly constructed in a scalable and lithography-free manner. Using IR spectroscopy, the selective and sensitive label-free detection of a molecular monolayer is achieved at a range of frequencies. An enhancement factor of nearly 10 5 is measured at the carbonyl (C = O) vibrational marker band of the molecule. The confluence of high field enhancement, broadband plasmonic response, and facile fabrication makes this metasurface a promising platform for SEIRA spectroscopy.

36 MATERIALS SCIENCE↗

Engineered Membrane Vesicle Production via oprF or oprI Deletion Has Distinct Phenotypic Effects in Pseudomonas putida

Membrane vesicle (MV) production is a natural phenomenon in Gram-negative bacteria and represents an emerging synthetic biology tool for the secretion of biomolecules or bioproducts. Manipulation of membrane components has proven successful in enhancing MV production. However, the impact of membrane disruptions on strain fitness and protein composition warrants further investigation for the use of MVs in industrial bioprocesses. Here, we identify and characterize two genetic engineering strategies for inducing hypervesiculation-deletion of genes for the outer membrane porin OprF or the lipoprotein OprI-in the commonly used platform Pseudomonas putida KT2440. Deletion of oprI generated up to a 1.5-fold increase in MVs, larger MVs with a greater proportion of outer membrane proteins, and no significant impact on strain fitness compared to wild type. In contrast, deletion of oprF, relative to wild type, generated up to a 4-fold increase in MVs but diminished growth, permeabilized membranes, and increased cytosolic protein packaging. Both hypervesiculation phenotypes increased nontargeted and MV-targeted mNeonGreen extracellular signal by up to 6-fold, demonstrating vesiculation as a mechanism for protein secretion. Despite increased blebbing of MVs from gene deletions, proteins involved in membrane biosynthesis were not elevated relative to wild type. Overexpression of gpsA, which initiates glycerophospholipid biosynthesis, in the ΔoprF background improved the membrane integrity by 37% and maintained MV formation, highlighting the importance of membrane biosynthesis in restoring the membrane in hypervesiculating strains. Together, this study provides genetic engineering strategies with corresponding phenotypic outcomes toward providing a synthetic biology toolset for MV deployment in P. putida.

59 BASIC BIOLOGICAL SCIENCES↗

Flow Regimes for Gas Migration in Liquid Stemming Columns

Some underground engineering projects require the design of an effective stemming column to confine pressurized gases within boreholes. While solid materials such as grout plugs are commonly used, their exothermic curing can damage diagnostic tools, particularly under harsh in situ conditions involving elevated pressure and temperature.

42 ENGINEERING↗

Correlating Time-Resolved Pressure Measurements With Rim Sealing Effectiveness for Real-Time Turbine Health Monitoring

Purge flow is bled from the upstream compressor and supplied to the under-platform region to prevent hot main gas path ingress that damages vulnerable under-platform hardware components. A majority of turbine rim seal research has sought to identify methods of improving sealing technologies and understanding the physical mechanisms that drive ingress. While these studies directly support the design and analysis of advanced rim seal geometries and purge flow systems, the studies are limited in their applicability to real-time monitoring required for condition-based operation and maintenance. As operational hours increase for in-service engines, this lack of rim seal performance feedback results in progressive degradation of sealing effectiveness, thereby leading to reduced hardware life. To address this need for rim seal performance monitoring, this study utilizes measurements from a one-stage turbine research facility operating with true-scale engine hardware at engine-relevant conditions. Time-resolved pressure measurements collected from the rim seal region are regressed with sealing effectiveness through the use of common machine learning techniques to provide real-time feedback of sealing effectiveness. Two modeling approaches are presented that use a single sensor to predict sealing effectiveness accurately over a range of two turbine operating conditions. Here, the results show that an initial purely data-driven model can be further improved using domain knowledge of relevant turbine operations, which yields sealing effectiveness predictions within 3% of measured values.

42 ENGINEERING↗

Tutorial: Lessons Learned for Behavior Analysts from Data Scientists

Big data is a computing term used to refer to large and complex data sets, typically consisting of terabytes or more of diverse data that is produced rapidly. The analysis of such complex data sets requires advanced analysis techniques with the capacity to identify patterns and abstract meanings from the vast data. The field of data science combines computer science with mathematics/statistics and leverages artificial intelligence, in particular machine learning, to analyze big data. This field holds great promise for behavior analysis, where both clinical and research studies produce large volumes of diverse data at a rapid pace (i.e., big data). This article presents basic lessons for the behavior analytic researchers and clinicians regarding integration of data science into the field of behavior analysis. We provide guidance on how to collect, protect, and process the data, while highlighting the importance of collaborating with data scientists to select a proper machine learning model that aligns with the project goals and develop models with input from human experts. Here, we hope this serves as a guide to support the behavior analysts interested in the field of data science to advance their practice or research, and helps them avoid some common pitfalls.

42 ENGINEERING↗

Correlating Time-Resolved Pressure Measurements With Rim Sealing Effectiveness for Real-Time Turbine Health Monitoring

Purge flow is bled from the upstream compressor and supplied to the under-platform region to prevent hot main gas path ingress that damages vulnerable under-platform hardware components. A majority of turbine rim seal research has sought to identify methods of improving sealing technologies and understanding the physical mechanisms that drive ingress. While these studies directly support the design and analysis of advanced rim seal geometries and purge flow systems, the studies are limited in their applicability to real-time monitoring required for condition-based operation and maintenance. As operational hours increase for in-service engines, this lack of rim seal performance feedback results in progressive degradation of sealing effectiveness, thereby leading to reduced hardware life. To address this need for rim seal performance monitoring, the present study utilizes measurements from a one-stage turbine research facility operating with true-scale engine hardware at engine-relevant conditions. Time-resolved pressure measurements collected from the rim seal region are regressed with sealing effectiveness through the use of common machine learning techniques to provide real-time feedback of sealing effectiveness. Two modelling approaches are presented that use a single sensor to predict sealing effectiveness accurately over a range of two turbine operating conditions. Results show that an initial purely data-driven model can be further improved using domain knowledge of relevant turbine operations, which yields sealing effectiveness predictions within three percent of measured values.

Compressors↗

Improving Low-Bandgap Tin–Lead Perovskite Solar Cells via Contact Engineering and Gas Quench Processing

Low-bandgap Sn/Pb ABX 3 perovskites have reached photovoltaic power conversion efficiencies >20%, but they usually have poor stability due to the common use of acidic poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS) hole transport layers and A-site cation compositions containing methylammonium (MA). In this work, we develop a process to enable high-quality MA-free Sn/Pb perovskite films grown using a gas quenching process instead of the conventional antisolvents, which provides improved control of the film growth and eliminates wrinkling. Using this method in a device structure with poly[bis(4-phenyl)(2,4,6-trimethylphenyl)amine] (PTAA) instead of PEDOT:PSS as the hole transport layer, devices can reach efficiencies up to 20% mppt at 0.06 cm 2 and up to 17.5% mppt at 1 cm 2 active area. With these improvements, the devices are characterized for thermal stability and show 80% of the initial power output remaining after 4000 h at 85 °C.

14 SOLAR ENERGY↗

Immunotargeting of Nanocrystals by SpyCatcher Conjugation of Engineered Antibodies

Inorganic nanocrystals such as quantum dots (QDs) and upconverting nanoparticles (UCNPs) are uniquely suited for quantitative live-cell imaging and are typically functionalized with ligands to study specific receptors or cellular targets. Antibodies (Ab) are among the most useful targeting reagents owing to their high affinities and specificities, but common nanocrystal labeling methods may orient Ab incorrectly, be reversible or denaturing, or lead to Ab-NP complexes too large for some applications. Here, we report that SpyCatcher proteins, which bind and spontaneously form covalent isopeptide bonds with cognate SpyTag peptides, can conjugate engineered Ab to nanoparticle surfaces with control over stability, orientation, and stoichiometry. Compact SpyCatcher-functionalized QDs and UCNPs may be labeled with short-chain variable fragment Ab (scFv) engineered to bind urokinase-type plasminogen activator receptors (uPAR) that are overexpressed in many human cancers. Confocal imaging of anti-uPAR scFv-QD conjugates shows the antibody mediates specific binding and internalization by breast cancer cells expressing uPAR. Time-lapse imaging of photostable scFv-UCNP conjugates shows that Ab binding causes uPAR internalization with a ~20 min half-life on the cell surface, and uPAR is internalized to endolysosomal compartments distinct from general membrane stains and without significant recycling to the cell surface. The controlled and stable conjugation of engineered Ab to NPs enables targeting of diverse receptors for live-cell study of their distribution, trafficking, and physiology.

60 APPLIED LIFE SCIENCES↗

High compressive energy absorption and shape recovery behavior of additively manufactured textile-inspired cylindrical braided metamaterials

Mechanical metamaterials (MMs) are engineered structures with unique mechanical properties that arise from their unique spatial arrangement or lattice-like structure. The most commonly designed MMs such as honeycomb and re-entrant auxetics are prone to failure at the sharp corners and weak joints due to the increased stress concentration under deformation. To mitigate this challenge, braided MM structures involving intertwining threads of nylon—forming curved unit cells—have been studied. These textile-inspired cylindrical braided metamaterials (CBMMs) with contrasting unit cells, namely diamond and regular CBMMs, were fabricated by 3D printing. The layer-by-layer deposited structure built by fused filament fabrication delivered an assembly of overlapped threads that are fused at the contact point. To understand deformation behavior of these MMs, finite element models were developed for various load scenarios including quasi-static compression, cyclic and creep loads at room temperature. Stress distribution, deformation mechanisms, and failure modes were analyzed and validated by experiments to analyze the geometries and associated performance. The diamond CBMMs showed stress softening at 30 % compressive strain, withstanding a load of ∼440 N, whereas the regular CBMMs at 50 % strain experienced ∼250 N. The diamond CBMMs delivered higher creep resistance under sustained load and better energy absorption under cyclic loading than the regular CBMMs. The latter, however, exhibited 94 % shape recovery in contrast to 88 % recovery in former prototype during their first cyclic load. In conclusion, this study helps design mechanical lightweight devices that endure significant sustained load and exhibit enhanced energy absorption and shape recovery characteristics in cyclic loading.

Creep↗

Stereomicrostructure-regulated biodegradable adhesives

Commercial adhesives are petroleum-based thermoset networks or nonbiodegradable thermoplastic hot melts, making them ideal targets for replacement by biodegradable alternatives. Poly(3-hydroxybutyrate) (P3HB) is a biorenewable and biodegradable alternative to conventional plastics, but microbial P3HB, which has a stereoperfect stereomicrostructure, exhibits no adhesion. Here, in this study, by elucidating the fundamental relationship between chemocatalytically engineered P3HB stereomicrostructures and adhesion properties, we found that biodegradable syndio-rich P3HB exhibits high adhesion strength and outperforms common commercial adhesives, whereas syndiotactic, isotactic, or iso-rich P3HB shows no measurable adhesion. The syndio-rich stereomicrostructure brings about desired thermomechanical and viscoelastic properties of P3HB that enable strong adhesion to a range of substrates tested, including aluminum, steel, glass, and wood, and its performance is insensitive to molar mass and reprocessing or reuse.

36 MATERIALS SCIENCE↗

Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C

Drainage structures are used to capture stormwater runoff in streets and highways in urban environments. These drainage structures, which typically consist of catch basins with grates, inlets, or combination grates/inlets, collect stormwater runoff and discharge through buried conveyance systems. They are strategically placed for public safety in curb and gutter systems to provide efficient drainage of water from roadways and thus reduce the risk of hydroplaning. The performance of drainage structures is measured in terms of hydraulic efficiency, which is defined as the percentage of flow captured by the basin as compared to the total flow drainage to the structure. Understanding of the performance of these drainage structures helps designers properly space inlets to promote an economic design that ensures the safety of the traveling public. The current design methodology used to determine drainage structure follows guidelines established in the current Michigan Department of Transportation (MDOT) Drainage Manual (2006). The guidelines in the MDOT Drainage Manual were modeled after the Federal Highway Administration’s (FHWA) Hydraulic Engineering Circular 22 “Urban Drainage Design” (HEC-22). HEC-22 includes empirically derived equations to calculate the interception capacity of drainage structures for several commonly used grate configurations, such as the parallel bar, curved vane and tilt bar grates, which are based on a research study performed by Burgi et al. in the 1970s. MDOT uses several drainage structures to capture runoff that are detailed as Standard Plans. Many of these drainage structures utilize sinusoidal type grates that are not described in HEC-22. Physical modeling of these structures has been limited, posing the need to have them analyzed to verify their capture efficiency. Current MDOT practice is to assume a similar sized reticuline grate, as described in HEC-22, for capture efficiencies. Until recently, evaluating the hydraulic performance of drainage structures was limited to physical modeling in a hydraulics laboratory. With advances in engineering software and computing power, computational fluid dynamics (CFD) modeling has become a more cost-effective alternative. The Federal Highway Administration (FHWA) provides states the option to evaluate their drainage structures using CFD through the Transportation Pooled Fund Program. This study, “Computational Analysis of Hydraulic Efficiency of Michigan DOT Cover C,” was carried out using the pooled fund. MDOT’s Cover C was chosen as the first test candidate, given its similar sinusoidal pattern to other MDOT grates, but it is typically used for high-volume, higher speed applications. A similar version, Cover CX, is used on interstate highways but does not have traverse bars for bicycle safety. Additional grates may be considered for evaluation in the future.

42 ENGINEERING↗

Quantifying thermal barrier coating delamination through luminescence modeling

Thermal barrier coatings (TBCs) are widely used in the hot sections of gas turbine systems as they are remarkably efficient in insulating the underlying superalloys, leading to higher operating temperatures and therefore enhancing the performance of the engines. However, this benefit is only possible if the integrity of the TBC under aggressive thermo-mechanical environments is ensured. Delamination is a common but hard to detect failure mode. We present, in this work, supported by experimentation, the implementation of a modeling approach applying the Kubelka-Munk theory to provide numerical quantification of luminescence contrast and intensity due to top coat delamination in TBCs. The method relies on the drastic change in reflectivity when a delamination forms, exploiting it for high-contrast luminescence mapping. Two distinct TBC configurations containing an erbium-doped yttria-stabilized zirconia (YSZ:Er 3+ ) layer for delamination sensing were used to validate this model. A delamination zone induced by Rockwell indentation was successfully tracked by measuring an increase of the intensity of the erbium emission line at 562 nm. Luminescence-based methods for delamination detection can provide a revolutionary non-invasive technique, with potential for both off-line and on-line engine monitoring.

36 MATERIALS SCIENCE↗

Development of Dy-free Nd-Fe-B-based sintered magnet through grain boundary engineering using Pr-Cu alloys

For this study, Dy-free sintered magnets were fabricated by mixing Nd-Fe-B powder with various amounts of Pr-Cu powder followed by the common procedures for making Nd-Fe-B based sintered magnets. With the Pr-Cu addition increasing from 0 to 10 wt.%, the obtained magnets’ H cj increases from the original 14.5 kOe to 18.6 kOe. The highest (BH) max achieved was 35.0 MGOe with 7.5 wt.% PrCu. The distribution of the Pr and Cu elements was primarily at grain boundary and triple junctions, leading to a reduced coupling among grains, thus an enhanced H cj .

36 MATERIALS SCIENCE↗

A constitutive framework for rocks undergoing solid dissolution

Here, we formulate a time-dependent damage theory for rocks subjected to mechanical deformation and solid dissolution. The constitutive description is inspired by the transition state theory, which states that the rate of dissolution is a function of the reactive surface area measured through the crack density in the volume. We use a gradient-enhanced damage framework in which damage depends on the deformation of the material as well as on the amount of solid mass dissolved over time. The gradient-enhanced formulation is characterized by a three-field variational formulation with the solid displacement, nonlocal equivalent strain, and nonlocal rate of solid dissolution as the basic state variables. Traditionally, time-independent damage theories have only allowed damage to increase with increasing external load. In the proposed framework, the degree of damage may increase due to solid dissolution even when the external load is held fixed. In this way, solid dissolution is viewed as a process that is responsible for bringing about rate-dependent effects such as creep and stress-relaxation, which are two common features of geomaterial behavior.

42 ENGINEERING↗