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At least 325 records · Page 18

Charge accumulation and solvation in $β$-NiOOH: Surface chemistry of an OER catalyst from ML-aided simulations

Electrochemical water splitting is a key technology for a sustainable energy transition, providing a route to store surplus electricity from renewable sources. A central bottleneck is the sluggish oxygen evolution reaction (OER), which drives the search for catalysts that are active, stable, and inexpensive enough for large-scale deployment. Within this context, pure and doped NiO x H y combine high activity with low cost, making them prime candidates for alkaline OER. Yet, despite extensive study, the atomistic structure of NiOOH under operando conditions and the associated reaction mechanisms remain debated. Here, we investigate the structural complexity of pure β-NiOOH, the scaffold for its doped derivatives. We systematically investigate the oxidation of the surface adsorbates via proton-coupled electron transfer steps across relevant facets and sites, identifying the most probable sequence of deprotonation events. Our results reveal asymmetric charge accumulation on Wulff-relevant surfaces and show how applied potential can promote morphological restructuring. Explicit solvation is included through machine-learning interatomic potential molecular dynamics of the NiOOH/water interface, which allows us to resolve the hydrophobic and hydrophilic character of different surfaces and the associated interfacial water structure. Together, these insights demonstrate how surface chemistry and solvation jointly govern the stability of NiOOH and the accumulation of surface charge, with possible implications for catalytic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Variability in Performance of a Machine Learning Seismicity Catalog: Central Italy, 2016–2017

Machine learning (ML) catalogs contain many more earthquakes than routine catalogs, but their performance in phase picking and earthquake detection has not been fully evaluated. We develop station‐level detection probabilities using logistic regression and combine them across a seismic network to compute spatial magnitude‐of‐completeness fields. We apply this approach to two catalogs from the 2016–2017 Central Italy sequence that were constructed from the same seismic network, one routine and one ML‐based. At the station level, the ML picker increases detection sensitivity by identifying smaller magnitude events and detecting earthquakes at greater distances. Spatially, the magnitude of completeness decreases substantially, with median values shifting from 1.6 to 0.5 for P waves and from 1.7 to 0.5 for S waves. However, the ML catalog also shows greater variability in station‐level performance than the routine catalog. These results demonstrate that ML‐based improvements in detectability are widespread but spatially nonuniform, highlighting their benefits, their limitations, and the potential for further improvements.

15 GEOTHERMAL ENERGY↗

The Geothermal Probabilistic Cost Model with an Application to a Geothermal Reservoir at Heber, California

A financial accounting model that incorporates physical and institutional uncertainties was developed for geothermal projects. Among the uncertainties it can handle are well depth, flow rate, fluid temperature, and permit and construction times. The outputs of the model are cumulative probability distributions of financial measures such as capital cost, levelized cost, and profit. These outputs are well suited for use in an investment decision incorporating risk. The model has the powerful feature that conditional probability distribution can be used to account for correlations among any of the input variables. The model has been applied to a geothermal reservoir at Heber, California, for a 45-MW binary electric plant. Under the assumptions made, the reservoir appears to be economically viable.

Orren, L. H.↗

Magnetic Field-Vector Measurements in Quiescent Prominences via the Hanle Effect: Analysis of Prominences Observed at Pic-Du-Midi and at Sacramento Peak

The Hanle effect method for magnetic field vector diagnostics has now provided results on the magnetic field strength and direction in quiescent prominences, from linear polarization measurements in the He I E sub 3 line, performed at the Pic-du-Midi and at Sacramento Peak. However, there is an inescapable ambiguity in the field vector determination: each polarization measurement provides two field vector solutions symmetrical with respect to the line-of-sight. A statistical analysis capable of solving this ambiguity was applied to the large sample of prominences observed at the Pic-du-Midi (Leroy, et al., 1984); the same method of analysis applied to the prominences observed at Sacramento Peak (Athay, et al., 1983) provides results in agreement on the most probable magnetic structure of prominences; these results are detailed. The statistical results were confirmed on favorable individual cases: for 15 prominences observed at Pic-du-Midi, the two-field vectors are pointing on the same side of the prominence, and the alpha angles are large enough with respect to the measurements and interpretation inaccuracies, so that the field polarity is derived without any ambiguity.

Bommier, V.↗

A method of classification for multisource data in remote sensing based on interval-valued probabilities

An axiomatic approach to intervalued (IV) probabilities is presented, where the IV probability is defined by a pair of set-theoretic functions which satisfy some pre-specified axioms. On the basis of this approach representation of statistical evidence and combination of multiple bodies of evidence are emphasized. Although IV probabilities provide an innovative means for the representation and combination of evidential information, they make the decision process rather complicated. It entails more intelligent strategies for making decisions. The development of decision rules over IV probabilities is discussed from the viewpoint of statistical pattern recognition. The proposed method, so called evidential reasoning method, is applied to the ground-cover classification of a multisource data set consisting of Multispectral Scanner (MSS) data, Synthetic Aperture Radar (SAR) data, and digital terrain data such as elevation, slope, and aspect. By treating the data sources separately, the method is able to capture both parametric and nonparametric information and to combine them. Then the method is applied to two separate cases of classifying multiband data obtained by a single sensor. In each case a set of multiple sources is obtained by dividing the dimensionally huge data into smaller and more manageable pieces based on the global statistical correlation information. By a divide-and-combine process, the method is able to utilize more features than the conventional maximum likelihood method.

Kim, Hakil↗

Recent advances in computational structural reliability analysis methods

The goal of structural reliability analysis is to determine the probability that the structure will adequately perform its intended function when operating under the given environmental conditions. Thus, the notion of reliability admits the possibility of failure. Given the fact that many different modes of failure are usually possible, achievement of this goal is a formidable task, especially for large, complex structural systems. The traditional (deterministic) design methodology attempts to assure reliability by the application of safety factors and conservative assumptions. However, the safety factor approach lacks a quantitative basis in that the level of reliability is never known and usually results in overly conservative designs because of compounding conservatisms. Furthermore, problem parameters that control the reliability are not identified, nor their importance evaluated. A summary of recent advances in computational structural reliability assessment is presented. A significant level of activity in the research and development community was seen recently, much of which was directed towards the prediction of failure probabilities for single mode failures. The focus is to present some early results and demonstrations of advanced reliability methods applied to structural system problems. This includes structures that can fail as a result of multiple component failures (e.g., a redundant truss), or structural components that may fail due to multiple interacting failure modes (e.g., excessive deflection, resonate vibration, or creep rupture). From these results, some observations and recommendations are made with regard to future research needs.

Thacker, Ben H.↗

PSC and volcanic aerosol routine observations in Antarctica by UV-visible ground-based spectrometry

Polar statospheric clouds (PSC) and stratospheric aerosol can be observed by ground-based UV-visible spectrometry by looking at the variation of the color of the sky during twilight. A radiative transfer model shows that reddenings are caused by high altitude (22-28 km) thin layers of scatterers, while low altitude (12-20 km) thick ones result in blueings. The color index method applied on 4 years of observations at Dumont d'Urville (67 deg S), from 1988 to 1991, shows that probably because the station is located at the edge of the vortex, dense PSC are uncommon. More unexpected is the existence of a systematic seasonal variation of the color of the twilight sky - bluer at spring - which reveals the formation of a dense scattering layer at or just above the tropopause at the end of the winter. Large scattering layers are reported above the station in 1991, first in August around 12-14 km, later in September at 22-24 km. They are attributed to volcanic aerosol from Mt Hudson and Mt Pinatubo respectively, which erupted in 1991. Inspection of the data shows that the lowest entered rapidly into the polar vortex but not the highest which remained outside, demonstrating that the vortex was isolated at 22-26 km.

Sarkissian, A.↗

A Rational Approach to Determine Minimum Strength Thresholds in Novel Structural Materials

Design of safe and survivable structures requires the availability of guaranteed minimum strength thresholds for structural materials to enable a meaningful comparison of strength requirement and available strength. This paper develops a procedure for determining such a threshold with a desired degree of confidence, for structural materials with none or minimal industrial experience. The problem arose in attempting to use a new, highly weight-efficient structural load tendon material to achieve a lightweight super-pressure balloon. The developed procedure applies to lineal (one dimensional) structural elements. One important aspect of the formulation is that it extrapolates to expected probability distributions for long length specimen samples from some hypothesized probability distribution that has been obtained from a shorter length specimen sample. The use of the developed procedure is illustrated using both real and simulated data.

Schur, Willi W.↗

An Efficient Approach for the Reliability Analysis of Phased-Mission Systems with Dependent Failures

We consider the reliability analysis of phased-mission systems with common-cause failures in this paper. Phased-mission systems (PMS) are systems supporting missions characterized by multiple, consecutive, and nonoverlapping phases of operation. System components may be subject to different stresses as well as different reliability requirements throughout the course of the mission. As a result, component behavior and relationships may need to be modeled differently from phase to phase when performing a system-level reliability analysis. This consideration poses unique challenges to existing analysis methods. The challenges increase when common-cause failures (CCF) are incorporated in the model. CCF are multiple dependent component failures within a system that are a direct result of a shared root cause, such as sabotage, flood, earthquake, power outage, or human errors. It has been shown by many reliability studies that CCF tend to increase a system's joint failure probabilities and thus contribute significantly to the overall unreliability of systems subject to CCF.We propose a separable phase-modular approach to the reliability analysis of phased-mission systems with dependent common-cause failures as one way to meet the above challenges in an efficient and elegant manner. Our methodology is twofold: first, we separate the effects of CCF from the PMS analysis using the total probability theorem and the common-cause event space developed based on the elementary common-causes; next, we apply an efficient phase-modular approach to analyze the reliability of the PMS. The phase-modular approach employs both combinatorial binary decision diagram and Markov-chain solution methods as appropriate. We provide an example of a reliability analysis of a PMS with both static and dynamic phases as well as CCF as an illustration of our proposed approach. The example is based on information extracted from a Mars orbiter project. The reliability model for this orbiter considers the various phases of Launch, Cruise, Mars Orbit Insertion, and Orbit. Some of the CCF for the orbiter in this mission include environmental effects, such as micrometeoroids, human operator errors, and software errors.

reliability analysis↗

Statistical Short-Range Guidance for Peak Wind Speed Forecasts at Edwards Air Force Base, CA

The peak winds near the surface are an important forecast element for space shuttle landings. As defined in the Flight Rules (FR), there are peak wind thresholds that cannot be exceeded in order to ensure the safety of the shuttle during landing operations. The National Weather Service Spaceflight Meteorology Group (SMG) is responsible for weather forecasts for all shuttle landings, and is required to issue surface average and 10-minute peak wind speed forecasts. They indicate peak winds are a challenging parameter to forecast. To alleviate the difficulty in making such wind forecasts, the Applied Meteorology Unit (AMU) developed a PC-based graphical user interface (GUI) for displaying peak wind climatology and probabilities of exceeding peak wind thresholds for the Shuttle Landing Facility (SLF) at Kennedy Space Center (KSC; Lambert 2003). However, the shuttle occasionally may land at Edwards Air Force Base (EAFB) in southern California when weather conditions at KSC in Florida are not acceptable, so SMG forecasters requested a similar tool be developed for EAFB.

Dreher, Joseph G.↗

Statistical Short-Range Guidance for Peak Wind Speed Forecasts at Edwards Air Force Base, CA

The peak winds near the surface are an important forecast element for Space Shuttle landings. As defined in the Shuttle Flight Rules (FRs), there are peak wind thresholds that cannot be exceeded in order to ensure the safety of the shuttle during landing operations. The National Weather Service Spaceflight Meteorology Group (SMG) is responsible for weather forecasts for all shuttle landings. They indicate peak winds are a challenging parameter to forecast. To alleviate the difficulty in making such wind forecasts, the Applied Meteorology Unit (AMTJ) developed a personal computer based graphical user interface (GUI) for displaying peak wind climatology and probabilities of exceeding peak-wind thresholds for the Shuttle Landing Facility (SLF) at Kennedy Space Center. However, the shuttle must land at Edwards Air Force Base (EAFB) in southern California when weather conditions at Kennedy Space Center in Florida are not acceptable, so SMG forecasters requested that a similar tool be developed for EAFB. Marshall Space Flight Center (MSFC) personnel archived and performed quality control of 2-minute average and 10-minute peak wind speeds at each tower adjacent to the main runway at EAFB from 1997- 2004. They calculated wind climatologies and probabilities of average peak wind occurrence based on the average speed. The climatologies were calculated for each tower and month, and were stratified by hour, direction, and direction/hour. For the probabilities of peak wind occurrence, MSFC calculated empirical and modeled probabilities of meeting or exceeding specific 10-minute peak wind speeds using probability density functions. The AMU obtained and reformatted the data into Microsoft Excel PivotTables, which allows users to display different values with point-click-drag techniques. The GUT was then created from the PivotTables using Visual Basic for Applications code. The GUI is run through a macro within Microsoft Excel and allows forecasters to quickly display and interpret peak wind climatology and likelihoods in a fast-paced operational environment. A summary of how the peak wind climatologies and probabilities were created and an overview of the GUT will be presented.

Dreher, Joseph↗

Demonstration of a Probabilistic Technique for the Determination of Economic Viability of Very Large Transport Configurations

Over the past few years, modem aircraft design has experienced a paradigm shift from designing for performance to designing for affordability. This report contains a probabilistic approach that will allow traditional deterministic design methods to be extended to account for disciplinary, economic, and technological uncertainty. The probabilistic approach was facilitated by the Fast Probability Integration (FPI) technique; a technique which allows the designer to gather valuable information about the vehicle's behavior in the design space. This technique is efficient for assessing multi-attribute, multi-constraint problems in a more realistic fashion. For implementation purposes, this technique is applied to illustrate how both economic and technological uncertainty associated with a Very Large Transport aircraft concept may be assessed. The assessment is evaluated with the FPI technique to determine the cumulative probability distributions of the design space, as bound by economic objectives and performance constraints. These distributions were compared to established targets for a comparable large capacity aircraft, similar in size to the Boeing 747-400. The conventional baseline configuration design space was determined to be unfeasible and marginally viable, motivating the infusion of advanced technologies, including reductions in drag, specific fuel consumption, wing weight, and Research, Development, Testing, and Evaluation costs. The resulting system design space was qualitatively assessed with technology metric "k" factors. The infusion of technologies shifted the VLT design into regions of feasibility and greater viability. The study also demonstrated a method and relationship by which the impact of new technologies may be assessed in a more system focused approach.

Mavris, Dimitri N.↗

Uncertainty Reduction using Bayesian Inference and Sensitivity Analysis: A Sequential Approach to the NASA Langley Uncertainty Quantification Challenge

This paper presents a computational framework for uncertainty characterization and propagation, and sensitivity analysis under the presence of aleatory and epistemic un- certainty, and develops a rigorous methodology for efficient refinement of epistemic un- certainty by identifying important epistemic variables that significantly affect the overall performance of an engineering system. The proposed methodology is illustrated using the NASA Langley Uncertainty Quantification Challenge (NASA-LUQC) problem that deals with uncertainty analysis of a generic transport model (GTM). First, Bayesian inference is used to infer subsystem-level epistemic quantities using the subsystem-level model and corresponding data. Second, tools of variance-based global sensitivity analysis are used to identify four important epistemic variables (this limitation specified in the NASA-LUQC is reflective of practical engineering situations where not all epistemic variables can be refined due to time/budget constraints) that significantly affect system-level performance. The most significant contribution of this paper is the development of the sequential refine- ment methodology, where epistemic variables for refinement are not identified all-at-once. Instead, only one variable is first identified, and then, Bayesian inference and global sensi- tivity calculations are repeated to identify the next important variable. This procedure is continued until all 4 variables are identified and the refinement in the system-level perfor- mance is computed. The advantages of the proposed sequential refinement methodology over the all-at-once uncertainty refinement approach are explained, and then applied to the NASA Langley Uncertainty Quantification Challenge problem.

Uncertainty↗

Probability Functions for Random Responses: Prediction of Peaks, Fatigue Damage, and Catastrophic Failures

This report reviews a number of theoretical matters in random process theory which can be applied to physical problems such as predicting peaks, structural fatigue damage, and catastrophic structural failures. The presentation emphasizes the basic assumptions which are involved, and discusses how to properly interpret the theoretical results. Various engineering examples are given as illustrations.

FATIGUE↗

Modifications to the Objective Lightning Probability Forecast Tool at Kennedy Space Center/Cape Canaveral Air Force Station, Florida

The 45th Weather Squadron (45 WS) at Cape Canaveral Air Force Station (CCAFS) includes the probability of lightning occurrence in their 24-Hour and Weekly Planning Forecasts, briefed at 0700 EDT for daily operations planning on Kennedy Space Center (KSC) and CCAFS. This forecast is based on subjective analyses of model and observational data and output from an objective tool developed by the Applied Meteorology Unit (AMU). This tool was developed over two phases (Lambert and Wheeler 2005, Lambert 2007). It consists of five equations, one for each warm season month (May-Sep), that calculate the probability of lightning occurrence for the day and a graphical user interface (GUI) to display the output. The Phase I and II equations outperformed previous operational tools by a total of 56%. Based on this success, the 45 WS tasked the AMU with Phase III to improve the tool further.

Crawford, Winifred↗

Chondrule formation, metamorphism, brecciation, an important new primary chondrule group, and the classification of chondrules

The recently proposed compositional classification scheme for meteoritic chondrules divides the chondrules into groups depending on the composition of their two major phases, olivine (or pyroxene) and the mesostasis, both of which are genetically important. The scheme is here applied to discussions of three topics: the petrographic classification of Roosevelt County 075 (the least-metamorphosed H chondrite known), brecciation (an extremely important and ubiquitous process probably experienced by greater than 40% of all unequilibrated ordinary chondrites), and the group A5 chondrules in the least metamorphosed ordinary chondrites which have many similarities to chondrules in the highly metamorphosed 'equilibrated' chondrites. Since composition provides insights into both primary formation properties of the chondruies and the effects of metamorphism on the entire assemblage it is possible to determine the petrographic type of RC075 as 3.1 with unique certainty. Similarly, the near scheme can be applied to individual chondrules without knowledge of the petrographic type of the host chondrite, which makes it especially suitable for studying breccias. Finally, the new scheme has revealed the existence of chondrules not identified by previous techniques and which appear to be extremely important. Like group A1 and A2 chondrules (but unlike group B1 chondrules) the primitive group A5 chondruies did not supercool during formation, but unlike group A1 and A2 chondrules (and like group B1 chondrules) they did not suffer volatile loss and reduction during formation. It is concluded that the compositional classification scheme provides important new insights into the formation and history of chondrules and chondrites which would be overlooked by previous schemes.

Sears, Derek W. G.↗

Inferences from protein and nucleic acid sequences - Early molecular evolution, divergence of kingdoms and rates of change

Description of new sensitive, objective methods for establishing the probable common ancestry of very distantly related sequences and the quantitative evolutionary change which has taken place. These methods are applied to four families of proteins and nucleic acids and evolutionary trees will be derived where possible. Of the three families containing duplications of genetic material, two are nucleic acids: transfer RNA and 5S ribosomal RNA. Both of these structures are functional in the synthesis of coded proteins, and prototypes must have been present in the cell at the inception of the fundamental coding process that all living things share. There are many types of tRNA which recognize the various nucleotide triplets and the 20 amino acids. These types are thought to have arisen as a result of many gene duplications. Relationships among these types are discussed. The 5S ribosomal RNA, presently functional in both eukaryotes and prokaryotes, is very likely descended from an early form incorporating almost a complete duplication of genetic material. The amount of evolution in the various lines can again be compared. The other two families containing duplications are proteins; ferredoxin and cytochrome c.

Dayhoff, M. O.↗

Compensated time of flight telescope for spaceborne cosmic ray measurements

A large area time-of-flight telescope has been studied for future application in space-borne cosmic ray experiments. A new compensation technique for propagation delays inside the scintillators has been applied, which is operative in two perpendicular directions. This technique, superior to conventional one-dimensional compensations, allows high rejection probability for upward moving single particles at very short counter distances. Besides mechanical advantages a short counter distance is desirable because it permits a large field of view for the detector. A measurement of light transit times in scintillators is presented and based on it, directionality for shower events is discussed.

Rothermel, H.↗