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At least 1,333 records · Page 74

NASA Engineering and Safety Center Technical Bulletin No. 15-02: Best Practices for Use of Sine Burst Testing

Sine Burst (SB) Testing is used for strength testing of aerospace hardware as an alternate to static pull and centrifuge tests. The main advantage is that testing can be implemented while hardware is on the shaker for other tests. It also imposes a lower number of cycles on the hardware compared with a sine dwell or sweep, and is particularly suitable for relatively stiff components or electronics boxes, instruments, or spacecraft. Identified risks can be mitigated by best practices.

Best Practices↗

The NREL Sensor Laboratory: Status and Future Directions for Hydrogen Detection

The NREL Hydrogen Sensor Laboratory was commissioned in 2010 as a resource for the national and international hydrogen community to ensure the availability and proper use of hydrogen sensors. Since then, the Sensor Laboratory has provided unbiased verification of hydrogen sensor performance for sensor developers, end-users, and regulatory agencies and has also provided active support for numerous code and standards development organizations. Although sensor performance assessment remains a core capability, the mission of the NREL Sensor Laboratory has expanded toward a more holistic approach regarding the role of hydrogen detection and its implementation strategy for both assurance of facility safety as well as for process control applications. Active monitoring for detection of unintended releases has been identified by the NFPA 2 Storage Task Group as a viable approach for improving facility safety and lowering setbacks. The current research program for the Sensor Laboratory addresses both conventional and advanced developing detection strategies in response to the emerging large-scale markets, such as those envisioned by H2@Scale. These emerging hydrogen applications may require alternative detection strategies that supplement and may ultimately supplant the use of traditional sensors for monitoring hydrogen releases. Research focus areas for the NREL Sensor Laboratory now encompasses the characterization of released hydrogen behavior to optimize detection strategies for both indoor and outdoor applications, advanced methods of hydrogen leak detection such as hydrogen wide area monitoring approaches for large scale and distributed applications, the incorporation of active monitoring as a risk reduction strategy to improve safety at hydrogen facilities, and continuing support of hydrogen safety codes and standards. In addition to assurance of safety, detection will be critical for process control applications, such as hydrogen fuel quality verification for fuel cell vehicle applications and for monitoring and controlling of hydrogen-natural gas blend composition.

codes and standards↗

ALD with Alternative Coreactants: Which Work, Which Do Not, and Why

In this paper, we present a combined experimental and theoretical study that systematically evaluates a series of alcohols (i.e., primary, secondary, and tertiary) as coreactants for trimethylaluminum (TMA)-based atomic layer deposition (ALD) of Al 2 O 3 . We employed in situ quartz crystal microbalance techniques and ex situ X-ray photoelectron spectroscopy to probe growth across a range of temperatures from T = 120 to 285 °C. Dispersion-inclusive hybrid density functional theory was employed to identify potential reaction pathways and compute corresponding Gibbs free-energy barriers and rate coefficients. Experimentally on an Al 2 O 3 surface, sustained thin-film growth, where the rate is constant over many cycles, was only observed with tertiary alcohols (tert-butanol and 2-methyl-2-butanol) at elevated temperatures (e.g., T = 285 °C); for tert-butanol specifically, sustained growth also occurred at T = 240 °C, with no sustained growth at or below T = 210 °C. Growth using primary and secondary alcohols decayed to a negligible value after only 2–3 cycles on an Al 2 O 3 surface at all tested temperatures. Intentional trace additions of H 2 O to anhydrous alcohols restored sustained growth but at reduced deposition rates relative to pure H 2 O. Theoretical analysis supports a bimolecular alkoxy β-H elimination mechanism as the primary reaction pathway: initiated by the formation of a bound alkoxy species, the subsequent β-H elimination step is rate-determining, with a barrier that systematically decreases as the degree of the alcohol coreactant is increased from primary to secondary to tertiary. Computed rate coefficients (k) also indicate a strong temperature dependence (with k increasing by ∼4–5 orders of magnitude from T = 120 to 285 °C) and are consistent with the experimental observation that only tertiary alcohols lead to steady thin-film growth at elevated temperatures. This integrated approach establishes why only certain alcohols can sustain Al 2 O 3 ALD and delivers a predictive framework for identifying effective alcohol coreactants.

36 MATERIALS SCIENCE↗

Integrated Design of Ultradurable, Low CO 2 Alternative Binder Systems via Machine Learning

This ARPA-E project developed a machine learning tool to use in formulation design of cementitious binders for concrete having 50% less embodied CO 2 and possessing twice the durability compared to concrete based on ordinary portland cement (OPC) binders. The technical focus was on limestone/calcined clay cement (LC3), the leading replacement for OPC. Here, hierarchical machine learning (HML) was used to model the flowability, set time, strength, and durability of LC3 concrete. This methodology identifies latent variables derived from domain knowledge and empirical models that develop an accurate model for a response surface from small datasets. For the flowability metric, particle packing was a dominant factor, while strength and durability were both strongly determined by the fraction of metakaolin and the water:solids ratio. Under constraints of water:binder ratio, material performance metrics, embodied CO 2 , and cost per tonne of OPC, multi-objective optimization was used to design binders parameterized by the mineral composition replacing OPC, particle size distributions, and water:solids ratio. The trained algorithm was able to predict multiple mixes met these performance criteria, and experimental testing validated the predictions. The model demonstrated here is relevant for North America, where pure kaolin deposits are found broadly. The approach is being taken forward into commercial application by Ansatz AI, a materials informatics company founded by PI Washburn and co-PI Poczos. Through collaborations with the cement and concrete industry, and funding from SBIR programs, a commercial software will be developed in future research.

36 MATERIALS SCIENCE↗

Colorado Alternatively Powered Aircraft Airport Infrastructure Study

Advanced Air Mobility encompasses emerging technologies in propulsion of general aviation and commuter aircraft for the purpose of moving passengers and goods. The State of Colorado has a strong aerospace and aviation legacy, and this research explores the potential energy implications of a transition from traditional aircraft propulsion systems to more-electric, full electric and hydrogen powered aircraft in flight schools, and small community air service utilizing NASA's Regional Air Mobility Model. Effort includes identifying potential energy needs and cost-effective solutions to support those emerging needs analyzing potential benefits on on-site generation and storage to optimize energy systems.Advanced Air Mobility encompasses emerging technologies in propulsion of general aviation and commuter aircraft for the purpose of moving passengers and goods. The State of Colorado has a strong aerospace and aviation legacy, and this research explores the potential energy implications of a transition from traditional aircraft propulsion systems to more-electric, full electric and hydrogen powered aircraft in flight schools, and small community air service utilizing NASA's Regional Air Mobility Model. Effort includes identifying potential energy needs and cost-effective solutions to support those emerging needs analyzing potential benefits on on-site generation and storage to optimize energy systems.

33 ADVANCED PROPULSION SYSTEMS↗

Archetypal TRMM Radar Profiles Identified Through Cluster Analysis

It is widely held that identifiable 'convective regimes' exist in nature, although precise definitions of these are elusive. Examples include land / Ocean distinctions, break / monsoon beahvior, seasonal differences in the Amazon (SON vs DJF), etc. These regimes are often described by differences in the realized local convective spectra, and measured by various metrics of convective intensity, depth, areal coverage and rainfall amount. Objective regime identification may be valuable in several ways: regimes may serve as natural 'branch points' in satellite retrieval algorithms or data assimilation efforts; one example might be objective identification of regions that 'should' share a similar 2-R relationship. Similarly, objectively defined regimes may provide guidance on optimal siting of ground validation efforts. Objectively defined regimes could also serve as natural (rather than arbitrary geographic) domain 'controls' in studies of convective response to environmental forcing. Quantification of convective vertical structure has traditionally involved parametric study of prescribed quantities thought to be important to convective dynamics: maximum radar reflectivity, cloud top height, 30-35 dBZ echo top height, rain rate, etc. Individually, these parameters are somewhat deficient as their interpretation is often nonunique (the same metric value may signify different physics in different storm realizations). Individual metrics also fail to capture the coherence and interrelationships between vertical levels available in full 3-D radar datasets. An alternative approach is discovery of natural partitions of vertical structure in a globally representative dataset, or 'archetypal' reflectivity profiles. In this study, this is accomplished through cluster analysis of a very large sample (0[107) of TRMM-PR reflectivity columns. Once achieved, the rainconditional and unconditional 'mix' of archetypal profile types in a given location and/or season provides a description of the local convective spectrum which retains vertical structure information. A further cluster analysis of these 'mixes' can identify recurrent convective spectra. These are a first step towards objective identification of convective regimes, and towards answering the question: 'What are the most convectively similar locations in the world?'

Boccippio, Dennis J.↗

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Fluorescence‐Based Transient Expression Assay for the Analysis of Upstream Open Reading Frames in Plants

Upstream open reading frames (uORFs) are regulatory elements present in the 5′ leaders of mRNA that can significantly impact downstream gene expression in eukaryotes. In crop engineering, editing of uORFs can provide an avenue to upregulate expression of native genes without the need to add persistent transgenic copies. Even with genome-wide methods to identify translated uORFs such as ribosome profiling, their functional characterization depends on validation through reporter gene assays and mutagenesis studies. Current screening methods for plants use luciferases or protoplasts to measure differential gene expression between wild-type and mutated transcript leaders, which requires tissue processing and/or substrate addition. Here, we present a time- and cost-efficient alternative to investigate transcript leaders by co-expression of two fluorescent proteins in Nicotiana benthamiana leaf tissue and test our assay on genes involved in photoprotection, editing of which could provide a pathway to increase CO 2 assimilation during sun–shade transitions.

Nicotiana benthamiana↗

Joint thrust and TMD resummation in electron-positron and electron-proton collisions

In this work, we present the framework for obtaining precise predictions for the transverse momentum of hadrons with respect to the thrust axis in e + e - collisions. This will enable a precise extraction of transverse momentum dependent (TMD) fragmentation functions from a recent measurement by the Belle Collaboration. Our analysis takes into account, for the first time, the nontrivial interplay between the hadron transverse momentum and the cut on the thrust event shape. To this end, we identify three different kinematic regions, derive the corresponding factorization theorems within Soft Collinear Effective Theory, and present all ingredients needed for the joint resummation of the transverse momentum and thrust spectrum at NNLL accuracy. One kinematic region can give rise to non-global logarithms (NGLs), and we describe how to include the leading NGLs. We also discuss alternative measurements in e + e - collisions that can be used to access the TMD fragmentation function. Finally, by using crossing symmetry, we obtain a new way to constrain TMD parton distributions, by measuring the displacement of the thrust axis in ep collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Assessing metal nitrides and metal carbides as supports for thermally stable single-atom catalysts

Single-atom catalysts supported on metal oxides have been demonstrated to exhibit exceptional activity while also maintaining single-atom stability. However, alternative supports such as metal nitrides and carbides have received far less attention. Herein, we use density functional theory to systematically investigate the relative thermal stability of single-atom catalysts over a host of transition metal nitride and carbide supports. By considering the binding and dimerization energies of isolated transition metal atoms across various surface facets, we identify transition metal/support pairs that show the most promise for high-density single-atom catalysts. We find that transition metal atoms can be stabilized on both defect sites and pristine surfaces over transition metal nitrides and carbides. Furthermore, we identify promising metal/support pairings that may be suitable for achieving both stable and high-density single-atom catalysts. Furthermore, these results provide valuable insights to guide synthesis efforts towards achieving stable single-atom transition metal catalysts.

Density functional theory↗

Utilization of coupled eigenmodes in Akiyama atomic force microscopy probes for bimodal multifrequency sensing

Akiyama atomic force microscopy probes represent a unique means of combining several of the desirable properties of tuning fork and cantilever probe designs. As a hybridized mechanical resonator, the vibrational characteristics of Akiyama probes result from a complex coupling between the intrinsic vibrational eigenmodes of its constituent tuning fork and bridging cantilever components. Here, through a combination of finite element analysis modeling and experimental measurements of the thermal vibrations of Akiyama probes, we identify a complex series of vibrational eigenmodes and measure their frequencies, quality factors, and spring constants. We then demonstrate the viability of Akiyama probes to perform bimodal multi-frequency force sensing by performing a multimodal measurement of a surface's nanoscale photothermal response using photo-induced force microscopy imaging techniques. Further performing a parametric search over alternative Akiyama probe geometries, we propose two modified probe designs to enhance the capability of Akiyama probes to perform sensitive bimodal multifrequency force sensing measurements.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

High Throughput Electrochemical Screening of Phosphate-Rich Nonflammable Electrolytes in Lithium-Ion Batteries

Frequent fires and explosions in lithium-ion batteries (LIBs) used in grid energy storage systems (ESS) highlight the necessity of revisiting nonflammable phosphate electrolytes as alternatives to the currently used flammable carbonates. However, previous studies have shown the difficulty of integrating phosphate solvents into LIB electrolytes due to compatibility issues with graphite. In this work, we developed a high-throughput (HTP) electrochemical characterization method, akin to pH test paper, to rapidly screen potential phosphate electrolytes and graphite materials. Through HTP screening, we identified 101 promising combinations out of 1,740. This number was reduced to 26 after testing in Li/Graphite half cells. The optimized phosphate-rich electrolyte (60 v% phosphate) with cosolvents demonstrated 300 stable cycles at 0.1 C in Graphite/LiFePO 4 (LFP) full cells with thick electrodes (∼3.0 mAh cm −2 ), surpassing prior research findings. This unique HTP method provides a powerful tool to expedite the development of safe LIBs for ESS applications.

25 ENERGY STORAGE↗

Sustainable Ethylene via Chemical Looping – Oxidative Dehydrogenation

This Phase I final report evaluates chemical looping–oxidative dehydrogenation as a lower-energy and cost-competitive alternative to conventional ethane steam cracking for ethylene production. The project combined catalyst development and experimental testing with process modeling, techno-economic analysis, and life-cycle assessment. Results indicate that the proposed process could improve olefin production, reduce energy use, and lower production costs, particularly when integrated with carbon capture and renewable electricity. The report also identifies remaining technical, environmental, and safety considerations and presents a technology maturation plan focused on longer-term catalyst evaluation and advancement toward pilot-scale demonstration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Synthetic fuels for ground transportation with special emphasis on hydrogen

The role of various synthetic fuels, for ground transportation in the United States, was examined for the near term (by 1985) and the longer term applications (1985-2000 and beyond 2000). Feasible options include synthetic oil, methanol, electric propulsion, and hydrogen. It is concluded that (1) the competition during the next 50 years will be for the fuels of all types, rather than among the fuels; (2) extensive domestic oil and gas exploration should be initiated concurrent with the development of several alternate fuels and related ancillaries; and (3) hydrogen, as an automotive fuel, seems to be equivalent to gasoline for optimum fuel to air mixtures. As a pollution free, high energy density fuel, hydrogen deserves consideration as the logical replacement for the hydrocarbons. Several research and development requirements, essential for the implementation of hydrogen economy for ground transportation, were identified. Extensive engineering development and testing activities should be initiated to establish hydrogen as the future automotive fuel, followed by demonstration projects and concerted efforts at public education.

Singh, J. J.↗

Input/output system identification - Learning from repeated experiments

The paper describes three approaches and possible variations for the determination of the Markov parameters for forced response data using general inputs. It is shown that, when the parameters in the solution procedure are bootstrapped, the results can be obtained very efficiently, but the errors propagate throughout all parameters. By arranging the data in a different form and using singular value decomposition, the resulting identified parameters are more accurate, in the least number of successive experiments, at the expense of a large matrix singular value decomposition. When a recursive procedure is employed, the calculations can be performed very efficiently, but the number of repetitions of the experiments is much greater for a given accuracy than for any of the previous approaches. An alternative formulation is proposed to combine the advantages of each of the approaches.

Juang, Jer-Nan↗

Interplanetary program to optimize simulated trajectories (IPOST). Volume 4: Sample cases

The Interplanetary Program to Optimize Simulated Trajectories (IPOST) is intended to support many analysis phases, from early interplanetary feasibility studies through spacecraft development and operations. The IPOST output provides information for sizing and understanding mission impacts related to propulsion, guidance, communications, sensor/actuators, payload, and other dynamic and geometric environments. IPOST models three degree of freedom trajectory events, such as launch/ascent, orbital coast, propulsive maneuvering (impulsive and finite burn), gravity assist, and atmospheric entry. Trajectory propagation is performed using a choice of Cowell, Encke, Multiconic, Onestep, or Conic methods. The user identifies a desired sequence of trajectory events, and selects which parameters are independent (controls) and dependent (targets), as well as other constraints and the cost function. Targeting and optimization are performed using the Standard NPSOL algorithm. The IPOST structure allows sub-problems within a master optimization problem to aid in the general constrained parameter optimization solution. An alternate optimization method uses implicit simulation and collocation techniques.

Hong, P. E.↗

Flow Visualization Proposed for Vacuum Cleaner Nozzle Designs

In 1995, the NASA Lewis Research Center and the Kirby Company (a major vacuum cleaner company) began negotiations for a Space Act Agreement to conduct research, technology development, and testing involving the flow behavior of airborne particulate flow behavior. Through these research efforts, we hope to identify ways to improve suction, flow rate, and surface agitation characteristics of nozzles used in vacuum cleaner nozzles. We plan to apply an advanced visualization technology, known as Stereoscopic Imaging Velocimetry (SIV), to a Kirby G-4 vacuum cleaner. Resultant data will be analyzed with a high-speed digital motion analysis system. We also plan to evaluate alternative vacuum cleaner nozzle designs. The overall goal of this project is to quantify both velocity fields and particle trajectories throughout the vacuum cleaner nozzle to optimize its "cleanability"--its ability to disturb and remove embedded dirt and other particulates from carpeting or hard surfaces. Reference

Source record↗