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At least 1,477 records · Page 82

Wettability of ultra-small pores of carbon electrodes by size-asymmetric ionic fluids

Recently, we studied the phase behavior of ionic fluids under confinement using the classical density functional theory within the framework of the restricted primitive model. Additionally, the theoretical results indicate that narrowing the pore size may lead to a drastic reduction in the electric double layer capacitance, while increasing the surface electrical potential would improve the ionic accessibility of micropores. In this work, we extend the theoretical investigation to systems containing size-asymmetric electrolytes that may exhibit a vapor-liquid like phase transition in the bulk phase. The effects of pore size and surface electric potential on the phase diagram and microscopic structures of the confined electrolytes were studied over a broad range of parameters. We found that decreasing the pore size or increasing the surface potential could destabilize the liquid phase in micropores, and capillary evaporation could occur regardless of the size asymmetry between cations and anions. Compared to that in a symmetric ionic system, the vapor-liquid phase separation is more likely to take place as the size asymmetry becomes more pronounced. The phase transition would alter the “accessibility” of ions to micropores and lead to coexisting micropores with different surface charge densities as identified by Monte Carlo simulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Parametric Finite Element Analysis of Naturally Corroded Steel Specimens Using 3D Surface Laser Scans

Corrosion is considered a uniform thickness reduction design guideline of the maritime industry. However, additionally, the corroded and irregular morphology of the surface affects the steel's load-bearing capacity and its impact on the strength and elongation behaviour of the steel is not yet fully understood. These effects on the local behaviour of steel structures under tensile loading were investigated with tensile tests on naturally corroded steel specimens and nonlinear finite element simulations including the corroded surface morphology with a uniform surface idealation. The models also include the deformed specimen shape. The developed approach led to highly accurate parametric finite element models predicting the ultimate tensile strength and longitudinal position of fracture. The results show that all included aspects are essential for accurate simulations, while solely the maximum available surface resolution was not as decisive.

corrosion↗

Summary of presentation for research on social structure, agreement, and conflict in groups in extreme and isolated environments

Despite a vast amount of research, little is known concerning the effect of group structure, and individuals' understanding of that structure, on conflict in Antarctic groups. The overall objective of the research discussed is to determine the interrelationships of group structure, social cognition, and group function and conflict in isolated and extreme environments. In the two decades following WWII, a large body of research focused on the physiological, psychological, and social psychological factors affecting the functioning of individuals and groups in a variety of extreme and isolated environments in both the Arctic and Antarctic. There are two primary reasons for further research of this type. First, Antarctic polar stations are considered to be natural laboratories for the social and behavioral sciences and provide an opportunity to address certain theoretical and empirical questions concerned with agreement and conflict in social groups in general and group behavior in extreme, isolated environments in particular. Recent advances in the analysis of social networks and intracultural variation have improved the methods and have shifted the theoretical questions. The research is motivated by three classes of questions: (1) What are the characteristics of the social relations among individuals working and living together in extreme and isolated environments?; (2) What do individuals understand about their group, how does that understanding develop, and how is it socially distributed?; and (3) What is the relationship between that understanding and the functioning of the social group? Answers to these questions are important if we are to advance our knowledge of how individuals and groups adapt to extreme environments. Second, although Antarctic winter-over candidates may be evaluated as qualified on the basis of individual characteristics, they may fail to adapt because of certain characteristics of the social group. Consequently, the ability of winter-over-groups to adapt to these extreme conditions has varied dramatically from year to year. In the past, differences in personality, background, and social status have led to conflicts between individuals or cliques precipitating, in turn, an overall decline in morale, failure to accomplish work tasks, and increases in insomnia, depression, anxiety, and alcohol abuse. A better understanding of the role of group structure and social cognition in processes of group adaptation and conflict in Antarctica would contribute towards the revision of existing screening methods, potentially leading to a reduction of group conflict and improved performance of scientific research and support activities. An improved screening protocol for the Antarctic would also have applications for other isolated environments such as scientific outposts and the proposed NASA space station. In sum, this research will (1) contribute significantly to our theoretical understanding of the role of social structure and cognition in the functioning of groups in isolation; (2) complement current work on health and adaptation in polar environments; and (3) provide for models of the formation of group structure that will aid in the development of improved procedures for assembling groups for the Antarctic and other isolated environments (e.g., space stations).

Source record↗

Input Shaping to Reduce Solar Array Structural Vibrations

Structural vibrations induced by actuators can be minimized using input shaping. Input shaping is a feedforward method in which actuator commands are convolved with shaping functions to yield a shaped set of commands. These commands are designed to perform the maneuver while minimizing the residual structural vibration. In this report, input shaping is extended to stepper motor actuators. As a demonstration, an input-shaping technique based on pole-zero cancellation was used to modify the Solar Array Drive Assembly (SADA) actuator commands for the Lewis satellite. A series of impulses were calculated as the ideal SADA output for vibration control. These impulses were then discretized for use by the SADA stepper motor actuator and simulated actuator outputs were used to calculate the structural response. The effectiveness of input shaping is limited by the accuracy of the knowledge of the modal frequencies. Assuming perfect knowledge resulted in significant vibration reduction. Errors of 10% in the modal frequencies caused notably higher levels of vibration. Controller robustness was improved by incorporating additional zeros in the shaping function. The additional zeros did not require increased performance from the actuator. Despite the identification errors, the resulting feedforward controller reduced residual vibrations to the level of the exactly modeled input shaper and well below the baseline cases. These results could be easily applied to many other vibration-sensitive applications involving stepper motor actuators.

Doherty, Michael J.↗

Vibroacoustic Characterization of Corrugated-Core and Honeycomb-Core Sandwich Panels

The vibroacoustic characteristics of two candidate launch vehicle fairing structures, corrugated- core and honeycomb-core sandwich designs, were studied. The study of these structures has been motivated by recent risk reduction efforts focused on mitigating high noise levels within the payload bays of large launch vehicles during launch. The corrugated-core sandwich concept is of particular interest as a dual purpose structure due to its ability to harbor resonant noise control systems without appreciably adding mass or taking up additional volume. Specifically, modal information, wavelength dispersion, and damping were determined from a series of vibrometer measurements and subsequent analysis procedures carried out on two test panels. Numerical and analytical modeling techniques were also used to assess assumed material properties and to further illuminate underlying structural dynamic aspects. Results from the tests and analyses described herein may serve as a reference for additional vibroacoustic studies involving these or similar structures.

Allen, Albert↗

Microbial Vessel for Impedance Spectroscopy and Electrochemistry (Mvise): an Extensible, Interoperable Data Acquisition Platform for Liquid Culture Studies in Space Biology Research

The White House Office of Science and Technology Policy (OSTP) has declared 2023 to be the Year of Open Science following an initiative to democratize scientific knowledge. Simultaneously, new sensor technologies have broadened the experimental space available to bioastronautics research. With these open-science goals and technological advances in mind, we have designed and constructed a data acquisition platform for high-precision, real-time monitoring of liquid culture systems. The vessel rig is fitted with six Atlas Scientific probes (micro pH, electrical conductivity, dissolved oxygen, oxidation-reduction potential, liquid temperature, air CO2) and a custom optical density probe similar to the one on BioSentinel’s BioSensor payload. A custom dielectric spectroscopy probe is also planned. The structure of the vessel is resin 3-D printed on a hobbyist-level machine, reducing the production cost and iteration time by over 60% each while increasing extensibility. Data acquisition and storage is controlled with a standalone C state machine-based program running on a Raspberry Pi 3 Model B. When not running headless, an additional program automatically generates and updates plots for live data visualization. Validation of the rig as a data collection system was performed with a yeast liquid culture experiment. While the vessel rig is currently used for standalone experiments, it can also be used as the base perception unit in a self-driving laboratory (SDL). SDLs are high-throughput data collection systems that employ automation and artificial intelligence to conduct and manage routine experiments. Here, we envision an SDL driven by several vessel rigs in which an automated script compares key results, informing the design of future experiments. A vessel rig SDL would streamline many operations, including 1) strain selection for the Lunar Explorer Instrument for space biology Applications (LEIA) investigation and 2) the study of bioregenerative life support systems (BLSS). Ultimately, the datasets that can now be acquired will provide crucial information for accelerating bioastronautics application development in the era of commercial space.

Stephen Lantin↗

Effects of Absorber Near-Interface Compensation on Cd(Se,Te) Solar Cell Performance

Arsenic (As) has been shown to be an effective p-type dopant for CdTe, although high performance in As-doped devices remains difficult to achieve. Arsenic is prone to self-compensation in CdTe, as evidenced by the accumulation of dopant atoms in CdTe/Cd(Se,Te) near the interface with MgxZn1-xO (MZO). In this study, we use SCAPS 1D modeling software to investigate the effect of near-interface compensation, helping elucidate loss pathways in present-day As-doped devices and informing future growth directions. We consider three possible results of As accumulation: shallow donors, deep recombination centers, and a thin layer of excess acceptor accumulation. The reduction in near-interface carrier concentration caused by shallow donors is shown to improve open-circuit voltages (VOC), whereas deep levels are detrimental to all performance parameters. The thin charge layer affects capacitance-voltage (CV) measurements by reducing the depletion width while maintaining the same carrier concentration, replicating CV behavior that has been observed in actual devices. These results illustrate the importance of monitoring dopant accumulation within 100 nm of the interface, and suggest that reducing or eliminating the As concentration in this region would be beneficial. An undoped Cd(Se,Te) layer at the interface is suggested as a possible device structure to boost performance.

absorber↗

Global energy sector emission reductions and bioenergy use: overview of the bioenergy demand phase of the EMF-33 model comparison

We present an overview of results from 11 integrated assessment models (IAMs) that participated in the 33rd study of the Stanford Energy Modeling Forum (EMF-33) on the viability of large-scale deployment of bioenergy for achieving long-run climate goals. The study explores future bioenergy use across models under harmonized scenarios for future climate policies, availability of bioenergy technologies, and constraints on biomass supply. This paper provides a more transparent description of IAMs that span a broad range of assumptions regarding model structures, energy sectors, and bioenergy conversion chains. Without emission constraints, we find vastly different CO 2 emission and bioenergy deployment patterns across models due to differences in competition with fossil fuels, the possibility to produce large-scale bio-liquids, and the flexibility of energy systems. Imposing increasingly stringent carbon budgets mostly increases bioenergy use. A diverse set of available bioenergy technology portfolios provides flexibility to allocate bioenergy to supply different final energy as well as remove carbon dioxide from the atmosphere by combining bioenergy with carbon capture and sequestration (BECCS). Sector and regional bioenergy allocation varies dramatically across models mainly due to bioenergy technology availability and costs, final energy patterns, and availability of alternative decarbonization options. Although much bioenergy is used in combination with CCS, BECCS is not necessarily the driver of bioenergy use. We find that the flexibility to use biomass feedstocks in different energy sub-sectors makes large-scale bioenergy deployment a robust strategy in mitigation scenarios that is surprisingly insensitive with respect to reduced technology availability. However, the achievability of stringent carbon budgets and associated carbon prices is sensitive. Constraints on biomass feedstock supply increase the carbon price less significantly than excluding BECCS because carbon removals are still realized and valued. Incremental sensitivity tests find that delayed readiness of bioenergy technologies until 2050 is more important than potentially higher investment costs.

09 BIOMASS FUELS↗

The origin and evolution of viruses inferred from fold family structure

The canonical frameworks of viral evolution describe viruses as cellular predecessors, reduced forms of cells, or entities that escaped cellular control. The discovery of giant viruses has changed these standard paradigms. Their genetic, proteomic and structural complexities resemble those of cells, prompting a redefinition and reclassification of viruses. In a previous genome-wide analysis of the evolution of structural domains in proteomes, with domains defined at the fold superfamily level, we found the origins of viruses intertwined with those of ancient cells. In this review, we extend these data-driven analyses to the study of fold families confirming the co-evolution of viruses and ancient cells and the genetic ability of viruses to foster molecular innovation. The results support our suggestion that viruses arose by genomic reduction from ancient cells and validate a co-evolutionary ‘symbiogenic’ model of viral origins.

59 BASIC BIOLOGICAL SCIENCES↗

Active Site Engineering via Optimizing the Heterogeneous Support Structure for Single-Atom Catalysis

Supported single-atom catalysts show a large range of activities and selectivities that depend on the local environment of the catalytic sites. Here a theory-based optimization strategy is presented that is based on a density functional theory determination of the transition states and intermediates for a low-dimensional coordinate representation of the heterogeneity of the active sites. The approach is applied to a vanadium catalyst on an amorphous SiO 2 support that involves a large kinetic network described using a full chemistry model. Without assuming a priori scaling relations or mechanism reduction, the optimal state of heterogeneity is found to lie at atomic configurations where the activation energies for two distinct key chemical processes are equal. It is found a posteriori that the behavior of the system is consistent with linear free energy scaling relations in the randomness parameters. The energetic span theory proves quite useful in reducing the full chemistry model to a small number of key reactions. The use of a nonlinear optimization algorithm in combination with energetic span theory provides significant simplification in treating disordered systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Physics-Based Data-Driven Approach for Modeling of Environmental Degradation in Elastomers

Abstract Elastomers are now commonly used in a number of industries, including aerospace, structure, transportation, shipbuilding, and automotive, due to their excellent workability, formability, and flexibility. During their activity, elastomers are subjected to harsh environmental conditions, which decreases their resilience. False predictions made early in their lives can have major financial and environmental implications. Elastomers’ performance and properties, such as strength, durability, and density, are influenced by chemical changes in these materials, known as degradation, which occurs over time. This process can alter the morphology of a polymer matrix as well as cause chain scission and cross-linking, resulting in different behaviors than that of the unaged material. To demonstrate the effect of thermaloxidative aging on the mechanical behavior of elastomers, several experimental and theoretical models have been proposed. In view of the large volume of experimental data available on micro-structural evolution in the course of aging, we propose a physics-based data-driven approach to overcome the shortcomings of both phenomenological and micro-mechanical models. This work presents a novel thermodynamically consistent, multiagent machine-learned model for predicting the constitutive behavior of cross-linked elastomers during environmental aging, such as thermo-oxidative and hydrolytic aging for various states of deformation. Single mechanism degradation changes the polymer matrix over time where it is causing chain scission, reduction of cross-links, and morphology change. To capture the idealized Mullins effect and permanent set due to the effect of single aging mechanisms on nonlinear mechanical responses of elastomers, we propose a data-driven model for simulating inelastic elements in a polymer matrix. By using a sequential order reduction, we were able to reduce the 3D stress-strain tensor mapping problem to a small number of super-constrained 1D mapping problems. To systematically classify such mapping problems into a few categories, an assembly of multiple replicated conditional neural network learning agents (L-agents) is used based on our recent work. Each category is represented by a different type of agent. The effect of deformation history, aging time, and aging temperature is captured by this model. The model is validated using a broad collection of data, ranging from our experimental results to data from the literature. In addition, thermodynamic consistency and frame independence are investigated. The most significant achievements of this model are its precision, simplicity, and prediction of inelasticity under various states of deformation. The model’s accuracy and simplicity make it a good option for commercial and industrial applications. Conveniently, due to the model modular nature, it can be expanded in the future to include viscoelasticity and non-isotropic formation for better precision.

Ghaderi, Aref↗

Changing circulation structure and precipitation characteristics in Asian monsoon regions: greenhouse warming vs. aerosol effects

Using model outputs from CMIP5 historical integrations, we have investigated the relative roles of anthropogenic emissions of greenhouse gases (GHG) and aerosols in changing the characteristics of the large-scale circulation and rainfall in Asian summer monsoon (ASM) regions. Under GHG warming, a strong positive trend in low-level moist static energy (MSE) is found over ASM regions, associated with increasing large-scale land–sea thermal contrast from 1870s to present. During the same period, a mid-tropospheric convective barrier (MCB) due to widespread reduction in relative humidity in the mid- and lower troposphere is strengthening over the ASM regions, in conjunction with expanding areas of anomalous subsidence associated with the Deep Tropical Squeeze (Lau and Kim in Proc Natl Acad Sci 12:3630–3635, 2015). The opposing effects of MSE and MCB lead to enhanced total ASM rainfall, but only a partial strengthening of the southern portion of the monsoon meridional circulation, coupled to anomalous multi-cellular overturning motions over ASM land. Including anthropogenic aerosol emissions strongly masks MSE but enhances MCB via increased stability in the lower troposphere, resulting in an overall weakened ASM circulation with suppressed rainfall. Analyses of rainfall characteristics indicate that under GHG, overall precipitation efficiency over the ASM region is reduced, manifesting in less moderate but more extreme heavy rain events. Under combined effects of GHG and aerosols, precipitation efficiency is unchanged, with more moderate, but less extreme rainfall.

54 ENVIRONMENTAL SCIENCES↗

Algorithms for real-time flutter identification

The work reported here addresses the important algorithm issues necessary to achieve a real-time flutter monitoring system; namely, the guidelines for choosing appropriate model forms, reduction of the parameter convergence transient, handling multiple modes, the effect of overparameterization, and estimate accuracy predictions, both online and for experiment design. An approach for efficiently computing continuous-time flutter parameter Cramer-Rao estimate error bounds has been developed. This enables a convincing comparison of theoretical and simulation results, as well as off-line studies in preparation for a flight test. Theoretical predictions, simulation and flight test results from the NASA/Dryden Drones for Aerodynamic and Structural Test (DAST) Program are compared.

Walker, R. A.↗

Real-time flutter analysis

The important algorithm issues necessary to achieve a real time flutter monitoring system; namely, the guidelines for choosing appropriate model forms, reduction of the parameter convergence transient, handling multiple modes, the effect of over parameterization, and estimate accuracy predictions, both online and for experiment design are addressed. An approach for efficiently computing continuous-time flutter parameter Cramer-Rao estimate error bounds were developed. This enables a convincing comparison of theoretical and simulation results, as well as offline studies in preparation for a flight test. Theoretical predictions, simulation and flight test results from the NASA Drones for Aerodynamic and Structural Test (DAST) Program are compared.

Walker, R.↗

Active control of propeller induced noise fields inside a flexible cylinder

An active noise control model has been evaluated for reducing aircraft interior noise. The structural noise transmission properties of an aircraft fuselage were modelled as a flexible cylinder excited by external acoustic dipoles simulating the noise produced by twin propellers. The amplitudes of an internal distribution of monopole control sources were determined such that the area-weighted mean square acoustic pressure was minimized in the propeller plane. The noise control model was evaluated at low frequencies corresponding to the blade passage frequency and first few harmonics of a typical turbo-prop aircraft. Interior noise reductions of 20 25 dB were achieved, over a substantial region of the cylindrical cross-section, with just a few monopole control sources. The most favorable interior noise reductions were achieved when the active noise control model was used in combination with propeller source phasing.

Lester, H. C.↗

Contributions of the Transonic Dynamics Tunnel to the Testing of Active Control of Aeroelastic Response

By the 1960s, researchers began to investigate the feasibility of using active controls technology (ACT) for increasing the capabilities of military and commercial aircraft. Since then many researchers, too numerous to mention, have investigated and demonstrated the usefulness of ACT for favorably modifying the aeroelastic response characteristics of flight vehicles. As a result, ACT entered the limelight as a viable tool for answering some very difficult design questions and had the potential for obtaining structural weight reductions optimizing maneuvering performance, and satisfying the multimission requirements being imposed on future military and commercial aircraft designs. Over the past 40 years, the NASA Langley Research Center (LaRC) has played a major role in developing ACT in part by its participation in many wind-tunnel programs conducted in the Transonic Dynamics Tunnel (TDT). These programs were conducted for the purposes of: (1) establishing concept feasibility; (2) demonstrating proof of concept; and (3) providing data for validating new modeling, analysis, and design methods. This paper provides an overview of the ACT investigations conducted in the TDT. For each program discussed herein, the objectives of the effort, the testing techniques, the test results, any, signIficant findings, and the lessons learned with respect to ACT testing are presented.

Perry, Boyd, III↗

Estimation of Model Error Variances During Data Assimilation

Data assimilation is all about understanding the error characteristics of the data and models that are used in the assimilation process. Reliable error estimates are needed to implement observational quality control, bias correction of observations and model fields, and intelligent data selection. Meaningful covariance specifications are obviously required for the analysis as well, since the impact of any single observation strongly depends on the assumed structure of the background errors. Operational atmospheric data assimilation systems still rely primarily on climatological background error covariances. To obtain error estimates that reflect both the character of the flow and the current state of the observing system, it is necessary to solve three problems: (1) how to account for the short-term evolution of errors in the initial conditions; (2) how to estimate the additional component of error caused by model defects; and (3) how to compute the error reduction in the analysis due to observational information. Various approaches are now available that provide approximate solutions to the first and third of these problems. However, the useful accuracy of these solutions very much depends on the size and character of the model errors and the ability to account for them. Model errors represent the real-world forcing of the error evolution in a data assimilation system. Clearly, meaningful model error estimates and/or statistics must be based on information external to the model itself. The most obvious information source is observational, and since the volume of available geophysical data is growing rapidly, there is some hope that a purely statistical approach to model error estimation can be viable. This requires that the observation errors themselves are well understood and quantifiable. We will discuss some of these challenges and present a new sequential scheme for estimating model error variances from observations in the context of an atmospheric data assimilation system.

Dee, Dick↗

Concepts and Development of Bio-Inspired Distributed Embedded Wired/Wireless Sensor Array Architectures for Acoustic Wave Sensing in Integrated Aerospace Vehicles

This paper discusses the modeling of acoustic emissions in plate structures and their sensing by embedded or surface bonded piezoelectric sensor arrays. Three different modeling efforts for acoustic emission (AE) wave generation and propagation are discussed briefly along with their advantages and disadvantages. Continuous sensors placed at right angles on a plate are being discussed as a new approach to measure and locate the source of acoustic waves. Evolutionary novel signal processing algorithms and bio-inspired distributed sensor array systems are used on large structures and integrated aerospace vehicles for AE source localization and preliminary results are presented. These systems allow for a great reduction in the amount of data that needs to be processed and also reduce the chances of false alarms from ambient noises. It is envisioned that these biomimetic sensor arrays and signal processing techniques will be useful for both wireless and wired sensor arrays for real time health monitoring of large integrated aerospace vehicles and earth fixed civil structures. The sensor array architectures can also be used with other types of sensors and for other applications.

Ghoshal, Anindya↗