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At least 199 records · Page 11

Melt extruded versus extrusion compression molded glass-polypropylene long fiber thermoplastic composites

Long fiber thermoplastic (LFT) composites are processed either with extrusion compression or fiber injection processes. The properties of LFT materials are highly influenced by processing techniques, which lead to different porosity contents, fiber length distributions, and fiber orientation distributions. It is important to understand the various LFT processing techniques and their effects on mechanical, thermal, and microscopic properties. This work considered LFT sheets processed via extrusion, which offers highly aligned fibers (referred to as “Tecnogor composites”), and LFT composites produced via extrusion compression molding (ECM), which offers a random distribution of fibers. Tecnogor composites exhibited higher flexural strength (35–65%), flexural modulus (132–172%), tensile strength (39–52%), tensile modulus (67–75%), and Izod impact resistance (195–220%) than the random LFT composites. This response was attributed to the aligned fibers in Tecnogor composites. Mathematical models including Halpin-Tsai and Lavengood-Goettler were used to predict and compare the Young’s modulus of Tecnogor and ECM composites, respectively.

mechanical testing↗

Equity-Centered Engagement Through Climate Resilience Policy in Massachusetts

Communities who experience disproportionate climate change impacts tend to be excluded from resilience planning (Vale, 2014). Those efforts typically follow top-down processes within established governance practices that are inaccessible to marginalized folks and reinforce inequalities (Malloy & Ashcraft, 2020; Adger, 2003). Such participatory planning processes may offer the public little opportunity to influence the process itself or the outcomes (Smith & McDonough, 2001). They might ignore important public values or alternative ways of knowing which can be critical assets in resilience (Few et al., 2007). Designing communities for climate action and resilience means creating opportunities for everyone to meaningfully shape those decisions and experience related benefits. Having the opportunity to shape one’s community is necessary for human flourishing (Allen, 2016). Resilience planning that shifts power into communities and focuses on social vulnerability can affect how people survive and thrive in a climate changed world. The Massachusetts Municipal Vulnerability Preparedness (MVP) 2.0 program is an attempt to change the status quo in resilience planning by bringing new voices into decision-making power, recognizing their labor, addressing root causes of vulnerability, and investing in social infrastructure. It aspires to build capacity for equity-focused community engagement within teams of municipal staff and community liaisons, and ultimately build social capital and community cohesion. My mixed methods research investigates implementation of this state grant program in several western Massachusetts towns. I am using document review, participant observation, and interviews to understand the MVP 2.0 process as written, how different towns navigate it, and how individuals make sense of their experiences in it. I seek to understand how those experiences explain relationships between engagement approaches, mediating factors, and process outcomes. I am interested in the conditions that allow for community empowerment and how a model like MVP 2.0 can shift conditions that hold systems in place. In a practical sense, our findings will help municipalities reflect on their work during MVP 2.0 and plan for future community engagement. They may be informative for designing future iterations of the MVP program and for other municipalities, offices of community engagement, and practitioners. The findings will also contribute to the participation, resilience, and climate justice literatures, by adding perspectives on equity-centered resilience and community engagement approaches in smaller towns and rural settings. References: Adger, W. N. (2003). Social capital, collective action, and adaptation to climate change. Economic Geography, 79, 387-404. Allen, D. (2016). Toward a connected society. Our compelling interests: The value of diversity for democracy and a prosperous society, 71-105. Few, R., Brown, K., & Tompkins, E. L. (2007). Public participation and climate change adaptation: avoiding the illusion of inclusion. Climate Policy, 7(1), 46–59. Malloy, J. T., & Ashcraft, C. M. (2020). A framework for implementing socially just climate adaptation. Climatic Change, 160(1), 1–14. Smith, P. D., & McDonough, M. H. (2001). Beyond public participation: Fairness in natural resource decision making. Society & natural resources, 14(3), 239-249. Vale, L. J. (2014). The politics of resilient cities: whose resilience and whose city? Building Research & Information, 42(2), 191–201.

Callaham, Shannon↗

Influence of Standard Image Processing of 3D X-ray Microscopy on Morphology, Topology and Effective Properties

Estimating porous media properties is a vital component of geosciences and the physics of porous media. Until now, imaging techniques have focused on methodologies to match image-derived flows or geomechanical parameters with experimentally identified values. Less emphasis has been placed on the compromise between image processing techniques and the consequences on topological and morphological characteristics and on computed properties such as permeability. The effects of some of the most popular image processing techniques (filtering and segmentation) available in open source on 3D X-ray Microscopy (micro-XRM) images are qualitatively and quantitatively discussed. We observe the impacts of various filters such as erosion-dilation and compare the efficiency of Otsu’s method of thresholding and the machine-learning-based software Ilastik for segmentation.

58 GEOSCIENCES↗

Failure of morphology of (0 deg)8 graphite/epoxy as influenced by environments and processing

Optical and scanning electron microscopy were used to investigate the failure morphology of graphite/epoxy specimens which had been tested until tensile failure. Failure morphology was studied as a function of the quality control variables of specimen preparation technique, prepreg batch, and cure condition, and also as a function of the environmental parameters of temperature and moisture content. Defective specimens were found to exhibit a low energy failure morphology. Poor specimen edge preparation and one batch of prepreg when tested at elevated temperature or moisture content also exhibited energy failure morphology. Postcuring had no effect on strength but did slightly alter failure morphology. Temperature or moisture appeared to decrease flaw sensitivity and thus increase strength; however, moisture also appeared to increase interfacial debonding between filament and matrix. When combined moisture and temperature increased interfacial debonding and made the epoxy matrix more prone to fracture.

Clements, L. L.↗

Long-term influence of physical aging processes in epoxy matrix composites

Selected mechanical properties of (plus or minus 45 degree sub 4s) graphite/epoxy composites were found to be affected by sub T sub g annealing. Postcured specimens of Thornel 300 graphite/Narmco 5208 epoxy were sub T sub G annealed at 413 K (140 C) for ca. 10 to the first through 10 to the fifth powers min., with a prior quenching from above T sub g. The ultimate tensile strength, strain-to-break, and toughness of the composite were found to decrease as a function of sub T sub g annealing time. The time-dependent change in properties can be explained on the basis of physical aging which is related to free volume changes in the non-equilibrium glassy state of network epoxies. The results imply possible changes in composite properties with service time.

Kong, E. S. W.↗

Influence of the equilibration process in supernova remnant shocks on their X-ray and coronal iron surface brightnesses

SNR model computation results have been obtained which indicate that the radial distribution of soft X-ray and forbidden coronal Fe surface brightnesses in adiabatic, middle-aged SNRs can be used as a basis of discrimination for whether the equilibration time is short or long, by comparison with the ionization time-scale. These models are based on a grid of Sedov-Taylor models with time-dependent, nonequilibrium collisional ionization of 13 chemical elements; the two extreme equilibration conditions assumed are T(ion) = T(e) and a Coulomb equilibration of ion and electron temperatures. The models are compared with data taken from X-ray images of the Cygnus Loop and Puppis A.

Jerius, D.↗

The influence of polar heterogeneous processes on reactive chlorine at middle latitudes - Three dimensional model implications

Three-dimensional model calculations with the NASA/GSFC chemistry and transport model have been designed to consider the impact of heterogeneous processes occurring on polar stratospheric clouds (PSCs) in the Arctic vortex on the HCl distribution. By examining the HCl concentration for a calculation with PSCs relative to a calculation with gas phase chemistry only, the impact of polar processing on reactive chlorine species at middle latitudes is inferred. Results from the chemistry and transport model reproduce basic features of the ClO measurements (Toohey et al., 1991), which were made on the ferry flights of the ER-2 from Stavanger, Norway to Moffett Field, California via Wallops Island, Virginia on February 20 and 21, 1989. The model indicates that perturbed air which is contained within the polar vortex during winter is not homogeneously mixed, and that the ferry flights were made through air with the largest conversion of HCl to reactive chlorine that is seen at middle latitudes.

Douglass, Anne R.↗

Influences of CO2 sublimation/condensation processes on the long-term evolution of the Martian atmosphere

The accumulation process of frozen CO2 within the Martian regolith is analyzed. The boundary conditions are taken to be the periodically variable temperature at the Mars surface and the constant heat flux at the bottom of the regolith layers, some hundred meters thick. The mean value of temperature as well as its amplitude are assumed to be dependent on latitude and could be variable with the geological time scale. The flux of gaseous CO2 within the regolith is controlled by the mechanism of gas transport through the porous medium. An appropriate initial geometry of distribution of pores is assumed. The porosity and flux change due to condensation/sublimation processes. The equations of heat and mass transfer are solved numerically for a given latitude. Next, the local (over the parallel of latitude belt) annual balance of CO2 is calculated. The procedure is repeated over the whole Martian surface and next the total annual net flux is calculated.

Kossacki, K.↗

The Role of Oceanic Processes in the Initiation of Boreal Winter Intraseasonal Oscillations Over the Indian Ocean

Observational analyses and ocean general circulation model experiments were performed to understand the influence of oceanic processes on warm sea surface temperature anomalies (SSTAs) prior to convection initiation of boreal winter intraseasonal oscillations (ISOs), including the Madden‐Julian Oscillation (MJO), in the tropical Indian Ocean. We found 39 strong ISOs that passed over the Indian Ocean Warm Pool (WP) region during the November–April season of the 2001–2012 period. Seventeen of them (44%) initiated over the Seychelles‐Chagos Thermocline Ridge (SCTR) before propagating eastward to the WP and Maritime Continent. Including only global‐scale MJOs, 71% (24%) of the remaining MJO events initiated from the SCTR (WP). Four (seven) SCTR (WP) ISO events were preceded by SSTAs that were strongly influenced by wind stress‐driven oceanic processes; all four (2/7) SCTR (WP) events were MJOs. Composite analyses of the four oceanic process influenced SCTR MJO events showed that wind stress‐driven oceanic processes contributed about 30% (between 0.1 and 0.2 °C) of the preconvection warming in the SCTR, which coincides with the Intertropical Convergence Zone with mean SST > 28 °C. Reduced upwelling and entrainment played a more important role than horizontal advection in elevating the +SSTAs. Case studies revealed that the two ocean process‐influenced primary MJO SCTR events were also associated with oceanic equatorial Rossby waves. Furthermore, results of a linear atmospheric mixed layer model indicated that boundary layer processes related to SSTAs contributed approximately half of the total convergence during MJO initiation, relative to the effect of the free troposphere, for the Rossby wave‐influenced events.

MJO Initiation↗

Optimal estimation for discrete time jump processes

Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are obtained. The approach is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. A general representation for optimum estimates and recursive equations for minimum mean squared error (MMSE) estimates are obtained. MMSE estimates are nonlinear functions of the observations. The problem of estimating the rate of a DTJP when the rate is a random variable with a probability density function of the form cx super K (l-x) super m and show that the MMSE estimates are linear in this case. This class of density functions explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.

Vaca, M. V.↗

Optimal estimation for discrete time jump processes

Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are derived. The approach used is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. Thus a general representation is obtained for optimum estimates, and recursive equations are derived for minimum mean-squared error (MMSE) estimates. In general, MMSE estimates are nonlinear functions of the observations. The problem is considered of estimating the rate of a DTJP when the rate is a random variable with a beta probability density function and the jump amplitudes are binomially distributed. It is shown that the MMSE estimates are linear. The class of beta density functions is rather rich and explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.

Vaca, M. V.↗

Thermomechanical behavior of amorphous tactic methacrylate polymers

Dynamic mechanical spectra of amorphous stereoregular poly(methyl methacrylate)s and poly(t-butyl methacrylate)s with assigned microtacticities are presented and discussed. An intermolecular argument is invoked to account for the higher glass transition temperature of syndiotactic vis a vis isotactic PMMA, in spite of the higher density of the latter at 30 C. An argument is presented to show that the ratio of glassy-region relaxation temperature to glass transition temperature is not only a measure of the degree of coupling of the beta and glass transition processes, but also of the degree to which intermolecular factors influence these processes. The greater extent of the low-temperature irreversibilities observed in the thermomechanical spectra of poly(t-butyl methacrylate)s is attributed to the brittle character induced by the bulky side groups which presumably weaken cohesive forces.

Kiran, E.↗

Why Is Improvement of Earth System Models so Elusive? Challenges and Strategies from Dust Aerosol Modeling

Past decades have seen an accelerating increase in computing efficiency, while climate models are representing a rapidly widening set of physical processes. Yet simulations of some fundamental aspects of climate like precipitation or aerosol forcing remain highly uncertain and resistant to progress. Dust aerosol modeling of soil particles lofted by wind erosion has seen a similar conflict between increasing model sophistication and remaining uncertainty. Dust aerosols perturb the energy and water cycles by scattering radiation and acting as ice nuclei, while mediating atmospheric chemistry and marine photosynthesis (and thus the carbon cycle). These effects take place across scales from the dimensions of an ice crystal to the planetary-scale circulation that disperses dust far downwind of its parent soil. Representing this range leads to several modeling challenges. Should we limit complexity in our model, which consumes computer resources and inhibits interpretation? How do we decide if a process involving dust is worthy of inclusion within our model? Can we identify a minimal representation of a complex process that is efficient yet retains the physics relevant to climate? Answering these questions about the appropriate degree of representation is guided by model evaluation, which presents several more challenges. How do we proceed if the available observations do not directly constrain our process of interest? (This could result from competing processes that influence the observed variable and obscure the signature of our process of interest.) Examples will be presented from dust modeling, with lessons that might be more broadly applicable. The end result will either be clinical depression or there assuring promise of continued gainful employment as the community confronts these challenges.

Climate models↗

Final Report On Non-Intrusive Load Monitoring Of Welding Processes

The conventional method of weld process monitoring is to monitor the process output electrical power close to the point of welding. Non-Intrusive Load Monitoring (NILM) describes the method of monitoring primary or utility electrical power into a welding process well away from the point of welding. The objective of this project was to determine if there is sufficient information within the welding process input power to understand process output power characteristics, and, if so, determine if there is sufficient resolution within the input electrical characteristics to infer some measures of weld quality. To understand the relationship between process input and output power, both input and output power were monitored for two welding processes (GMAW and GTAW) and two different power source types (inverter and SCR). Welds were made with and without intentional disturbances. The results showed that there is a strong correlation between input and output power and that the influence of process disturbances are evident within the input power. A simple method using input power only was devised and successfully demonstrated to discriminate between a weld made with no intentional disturbance (a nominal weld) from a weld made with an intentional disturbance (off-nominal weld). The primary conclusions of this work is that NILM of process input power is sensitive to process disturbances that could influence weld quality and that the approach warrants additional study.

36 MATERIALS SCIENCE↗

Maximum respiration rates in hyporheic zone sediments are primarily constrained by organic carbon concentration and secondarily by organic matter chemistry

Abstract. River corridors are fundamental components of the Earth system, and their biogeochemistry can be heavily influenced by processes in subsurface zones immediately below the riverbed, referred to as the hyporheic zone. Within the hyporheic zone, organic matter (OM) fuels microbial respiration, and OM chemistry heavily influences aerobic and anaerobic biogeochemical processes. The link between OM chemistry and respiration has been hypothesized to be mediated by OM molecular diversity, whereby respiration is predicted to decrease with increasing diversity. Here we test the specific prediction that aerobic respiration rates will decrease with increases in the number of unique organic molecules (i.e., OM molecular richness, as a measure of diversity). We use publicly available data across the United States from crowdsourced samples taken by the Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS) consortium. Our continental-scale analyses rejected the hypothesis of a direct limitation of respiration by OM molecular richness. In turn, we found that organic carbon (OC) concentration imposes a primary constraint over hyporheic zone respiration, with additional potential influences of OM richness. We specifically observed respiration rates to decrease nonlinearly with the ratio of OM richness to OC concentration. This relationship took the form of a constraint space with respiration rates in most systems falling below the constraint boundary. A similar, but slightly weaker, constraint boundary was observed when relating respiration rate to the inverse of OC concentration. These results indicate that maximum respiration rates may be governed primarily by OC concentration, with secondary influences from OM richness. Our results also show that other variables often suppress respiration rates below the maximum associated with the richness-to-concentration ratio. An important focus of future research will identify physical (e.g., sediment grain size), chemical (e.g., nutrient concentrations), and/or biological (e.g., microbial biomass) factors that suppress hyporheic zone respiration below the constraint boundaries observed here.

58 GEOSCIENCES↗

Stream Temperature Prediction in a Shifting Environment: Explaining the Influence of Deep Learning Architecture

Stream temperature is a fundamental control on ecosystem health. Recent efforts incorporating process guidance into deep learning models for predicting stream temperature have been shown to outperform existing statistical and physical models. This performance is in part because deep learning architectures can actively learn spatiotemporal relationships that govern how water and energy propagate through a river network. However, exploration of how spatiotemporal awareness and process guidance influence a model's generalizability under shifting environmental conditions such as climate change is limited. Here, we use Explainable Artificial Intelligence (XAI) to interrogate how differing deep learning architectures affect a model's learned spatial and temporal dependencies, and how those learned dependencies affect a model's ability to maintain high accuracy when applied to unseen environmental conditions. Using the Delaware River Basin in the northeastern United States as a test case, we compare two spatiotemporally aware process–guided deep learning models for predicting stream temperature (a recurrent graph convolution network—RGCN, and a temporal convolution graph model—Graph WaveNet). Both models achieve equally high predictive performance when testing data are well represented in the training data (test root mean squared errors of 1.64°C and 1.65°C); however, Graph WaveNet significantly outperforms RGCN in 4 out of 5 experiments where test partitions represent different types of unseen environmental conditions. XAI results show that the architecture of Graph WaveNet leads to learned spatial relationships with greater fidelity to physical processes, and that this fidelity improves the generalizability of the model when applied to shifting and/or unseen environmental conditions.

54 ENVIRONMENTAL SCIENCES↗