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48 records · Page 3

Comparisons of various configurations of the edge delamination test for interlaminar fracture toughness

Various configurations of Edge Delamination Tension (EDT) test specimens, of both brittle (T300/5208) and toughened-matrix (T300/BP907) graphite reinforced composite laminates, were manufactured and tested. The mixed-mode interlaminar fracture toughness, G sub C, was measured using (30/30 sub 2/30/90 sub N)sub s, n=1 or 2, (35/-35/0/90) sub s and (35/0/-35/90) sub s layups designed to delaminate at low tensile strains. Laminates were made without inserts so that delaminations would form naturally between the central 90 deg plies and the adjacent angle plies. Laminates were also made with Teflon inserts implanted between the 90 deg plies and the adjacent angle (theta) plies at the straight edge to obtain a planar fracture surface. In addition, interlaminar tension fracture toughness, GIc, was measured from laminates with the same layup but with inserts in the midplane, between the central 90 deg plies, at the straight edge. All of the EDT configurations were useful for ranking the delamination resistance of composites with different matrix resins. Furthermore, the variety of layups and configurations available yield interlaminar fracture toughness measurements needed to generate delamination failure criteria. The influence of insert thickness and location, and coupon size on G sub c values were evaluated.

Obrien, T. K.↗

Synthesis and stability of Br2, ICl and IBr intercalated pitch-based graphite fibers

The intercalation of halogens in pitch-based fiber is studied as well as the stability of the resultant intercalation compounds. It is found that IBr intercalates P-100 to yield a high-sigma GIC with attractive stability properties. During ICl intercalation, the presence of O2 interferes with the reaction and necessitates a higher threshold pressure for intercalation.

Wessbecher, Dorothy E.↗

The real-time learning mechanism of the Scientific Research Associates Advanced Robotic System (SRAARS)

Scientific research associates advanced robotic system (SRAARS) is an intelligent robotic system which has autonomous learning capability in geometric reasoning. The system is equipped with one global intelligence center (GIC) and eight local intelligence centers (LICs). It controls mainly sixteen links with fourteen active joints, which constitute two articulated arms, an extensible lower body, a vision system with two CCD cameras and a mobile base. The on-board knowledge-based system supports the learning controller with model representations of both the robot and the working environment. By consecutive verifying and planning procedures, hypothesis-and-test routines and learning-by-analogy paradigm, the system would autonomously build up its own understanding of the relationship between itself (i.e., the robot) and the focused environment for the purposes of collision avoidance, motion analysis and object manipulation. The intelligence of SRAARS presents a valuable technical advantage to implement robotic systems for space exploration and space station operations.

Chen, Alexander Y.↗

Radial Breathing Modes in Cosmochemistry and Meteoritics

One area of continuing interest in cosmochemistry and meteoritics (C&M) is the identification of the nature of Q-phase, although some researchers in C&M are not reporting relevant portions of Raman spectral data. Q is the unidentified carrier of noble gases in carbonaceous chondrites (CCs). Being carbonaceous, the focus has been on any number of Q-candidates arising from the sp2 hybridization of carbon (C). These all derive from various forms of graphene, a monolayer of C atoms packed into a two-dimensional (2D) hexagonal honeycomb lattice that is the basic building block for graphitic materials of all other dimensions for sp2 allotropes of C. As a basic lattice, 2D graphene can be curled into fullerenes (0D), wrapped into carbon nanotubes or CNTs (1D), and stacked into graphite (3D). These take such additional forms as scroll-like carbon whiskers, carbon fibers, carbon onions, GPCs (graphite polyhedral crystals) [6], and GICs (graphite intercalation compounds). Although all of these have been observed in meteoritics, the issue is which can explain the Q-abundances. In brief, one or more of the 0D-3D sp2 hybridization forms of C is Q. For some Q-candidates, the radial breathing modes (RBMs) are the most important Raman active vibrational modes that exist, and bear a direct relevance to solving this puzzle. Typically in C&M they are ignored when present. Their importance is addressed here as smoking-gun signatures for certain Q-candidates and are very relevant to the ultimate identification of Q.

Wilson, T.L.↗

Forecasting Propagation and Evolution of CMEs in an Operational Setting: What Has Been Learned

One of the major types of solar eruption, coronal mass ejections (CMEs) not only impact space weather, but also can have significant societal consequences. CMEs cause intense geomagnetic storms and drive fast mode shocks that accelerate charged particles, potentially resulting in enhanced radiation levels both in ions and electrons. Human and technological assets in space can be endangered as a result. CMEs are also the major contributor to generating large amplitude Geomagnetically Induced Currents (GICs), which are a source of concern for power grid safety. Due to their space weather significance, forecasting the evolution and impacts of CMEs has become a much desired capability for space weather operations worldwide. Based on our operational experience at Space Weather Research Center at NASA Goddard Space Flight Center (http://swrc.gsfc.nasa.gov), we present here some of the insights gained about accurately predicting CME impacts, particularly in relation to space weather operations. These include: 1. The need to maximize information to get an accurate handle of three-dimensional (3-D) CME kinetic parameters and therefore improve CME forecast; 2. The potential use of CME simulation results for qualitative prediction of regions of space where solar energetic particles (SEPs) may be found; 3. The need to include all CMEs occurring within a ~24 h period for a better representation of the CME interactions; 4. Various other important parameters in forecasting CME evolution in interplanetary space, with special emphasis on the CME propagation direction. It is noted that a future direction for our CME forecasting is to employ the ensemble modeling approach.

forecasting↗

Fracture Toughness of Carbon Fiber Composites Containing Various Fiber Sizings and a Puncture Self-Healing Thermoplastic Matrix

Ongoing efforts at NASA Langley Research Center (LaRC) have resulted in the identification of several commercially available thermoplastic resin systems which self-heal after ballistic impact and through penetration. One of these resins, polybutylene graft copolymer (PBg), was selected as a matrix for processing with unsized carbon fibers to fabricate reinforced composites for further evaluation. During process development, data from thermo-physical analyses was utilized to determine a processing cycle to fabricate laminate panels, which were analyzed by photo microscopy and acid digestion. The process cycle was further optimized based on these results to fabricate panels for mechanical property characterization. The results of the processing development effort of this composite material, as well as the results of the mechanical property characterization, indicated that bonding between the fiber and PBg was not adequate. Therefore, three sizings were investigated in this work to assess their potential to improve fiber/matrix bonding compared to previously tested unsized IM7 fiber. Unidirectional prepreg was made at NASA LaRC from three sized carbon fibers and utilized to fabricate test coupons that were tested in double cantilever beam configurations to determine GIc fracture toughness.

Cano, Roberto J.↗

Space Weather Products and Tools Used in Auroral Monitoring and Forecasting at CCMC/SWRC

Key points discussed in this chapter are (1) the importance of aurora research to scientific advances and space weather applications, (2) space weather products at CCMC that are relevant to aurora monitoring and forecasting, and (3) the need for more effort from the whole community to achieve a better and long‐lead‐time forecast of auroral activity. Aurora, as manifestations of solar wind−magnetosphere−ionosphere coupling that occurs in a region of space that is relatively easy to access for sounding rockets, satellites, and other types of observational platforms, serves as a natural laboratory for studying the underlying physics of the complex system. From a space weather application perspective, auroras can cause surface charging of technological assets passing through the region, result in scintillation effects affecting communication and navigation, and cause radar cluttering that hinders military and civilian applications. Indirectly, an aurora and its currents can induce geomagnetically induced currents (GIC) on the ground, which poses major concerns for the wellbeing and operation of power grids, particularly during periods of intense geomagnetic activity. In addition, accurate auroral forecasting is desired for auroral tourism. In this chapter, we first review some of the existing auroral models and discuss past validation efforts. Such efforts are crucial in transitioning a model(s) from research to operations and for further model improvement and development that also benefits scientific endeavors. Then we will focus on products and tools that are used for auroral monitoring and forecasting at the Space Weather Research Center (SWRC). As part of the CCMC (Community Coordinated Modeling Center), SWRC has been providing space weather services since 2010.

Zheng, Yihua↗

Space Weather Products and Tools Used in Auroral Monitoring and Forecasting at CCMC/SWRC

Key points discussed in this chapter are (1) the importance of aurora research to scientific advances and space weather applications, (2) space weather products at CCMC that are relevant to aurora monitoring and forecasting, and (3) the need for more effort from the whole community to achieve a better and long-lead- time forecast of auroral activity. Aurora, as manifestations of solar wind-magnetosphere-ionosphere coupling that occurs in a region of space that is relatively easy to access for sounding rockets, satellites, and other types of observational platforms, serves as a natural laboratory for studying the underlying physics of the complex system. From a space weather application perspective, auroras can cause surface charging of technological assets passing through the region, result in scintillation effects affecting communication and navigation, and cause radar cluttering that hinders military and civilian applications. Indirectly, an aurora and its currents can induce geomagnetically induced currents (GIC) on the ground, which poses major concerns for the wellbeing and operation of power grids, particularly during periods of intense geomagnetic activity. In addition, accurate auroral forecasting is desired for auroral tourism. In this chapter, we first review some of the existing auroral models and discuss past validation efforts. Such efforts are crucial in transitioning a model(s) from research to operations and for further model improvement and development that also benefits scientific endeavors. Then we will focus on products and tools that are used for auroral monitoring and forecasting at the Space Weather Research Center (SWRC). As part of the CCMC (Community Coordinated Modeling Center), SWRC has been providing space weather services since 2010.

Zheng, Yihua↗

Multi-Variate LSTM Prediction of Alaska Magnetometer Chain Utilizing a Coupled Model Approach

During periods of rapidly changing geomagnetic conditions electric fields form within the Earth’s surface and induce currents known as geomagnetically induced currents(GICs), which interact with unprotected electrical systems our society relies on. In this study, we train multi-variate Long-Short Term Memory neural networks to predict magnitude of north-south component of the geomagnetic field (|BN|) at multiple ground magnetometer stations across Alaska provided by the SuperMAG database with a future goal of predicting geomagnetic field disturbances. Each neural network is driven by solar wind and interplanetary magnetic field inputs from the NASA OMNI database spanning from 2000–2015 and is fine tuned for each station to maximize the effectiveness in predicting |BN|. The neural networks are then compared against multivariate linear regression models driven with the same inputs at each station using Heidke skill scores with thresholds at the 50, 75, 85, and 99 percentiles for |BN|. The neural network models show significant increases over the linear regression models for |BN| thresholds. We also calculate the Heidke skill scores for d|BN|/dt by deriving d|BN|/dt from |BN| predictions. However, neural network models do not show clear outperformance compared to the linear regression models. To retain the sign information and thus predict BN instead of |BN|, a secondary so-called polarity model is utilized. The polarity model is run in tandem with the neural networks predicting geomagnetic field in a coupled model approach and results in a high correlation between predicted and observed values for all stations. We find this model a promising starting point for a machine learned geomagnetic field model to be expanded upon through increased output time history and fast turnaround times.

Matthew Blandin↗

Space Weather: From Solar Origins to Risks and Hazards Evolving in Time

Space Weather is the portion of space physics that has a direct effect onhumankind. Space Weather is an old branch of space physics that originatesback to 1808 with the publication of a paper by the great naturalist Alexandervon Humboldt (Von Humboldt, Ann. Phys. 1808, 29, 425–429),first defining a“Magnetische Ungewitter”or magnetic storm from auroral observations fromhis home in Berlin, Germany. Space Weather is currently experiencing explosivegrowth, because its effects on human technologies have become more andmore diverse. Space Weather is due to the variability of solar processes thatcause interplanetary, magnetospheric, ionospheric, atmospheric and groundlevel effects. Space Weather can at times have strong impacts on technologicalsystems and human health. The threats and risks are not hypothetical, and in theevent of extreme Space Weather events the consequences could be quitesevere for humankind. The purpose of the review is to give a brief overall view ofthe full chain of physical processes responsible for Space Weather risks andhazards, tracing them from solar origins to effects and impacts in interplanetaryspace, in the Earth’s magnetosphere and ionosphere and at the ground. Inaddition, the paper shows that the risks associated with Space Weather have notbeen constant over time; they have evolved as our society becomes more andmore technologically advanced. The paper begins with a brief introduction tothe Carrington event, arguably the greatest geomagnetic storm in recordedhistory. Next, the descriptions of the strongest known Space Weather processesare reviewed, tracing them from their solar origins. The concepts ofgeomagnetic storms and substorms are briefly introduced. The main effects/impacts of Space Weather are also considered, including geomagneticallyinduced currents (GICs) which are thought to cause power outages. Theeffects of radiation on avionics and human health, ionospheric effects andimpacts, and thermosphere effects and satellite drag will also be discussed.Finally, we will discuss the current challenges of Space Weather forecasting andexamine some of the worst-case scenarios.

Natalia Buzulukova↗

Exploring Localized Geomagnetic Disturbances in Global MHD: Physics and Numerics

One of the prominent effects of space weather is the formation of rapid geomagnetic field variations on Earth's surface driven by the magnetosphere-ionosphere system. These geomagnetic disturbances (GMDs) cause geomagnetically induced currents to run through ground conducting systems. In particular, localized GMDs (LGMDs) can be high amplitude and can have an effect on scale sizes less than 100 km, making them hazardous to power grids and difficult to predict. In this study, we examine the ability of the Space Weather Modeling Framework (SWMF) to reproduce LGMDs in the 7 September 2017 event using both existing and new metrics to quantify the success of the model against observation. We show that the high-resolution SWMF can reproduce LGMDs driven by ionospheric sources, but struggles to reproduce LGMDs driven by substorm effects. We calculate the global maxima of the magnetic fluctuations to show instances when the SWMF captures LGMDs at the correct times but not the correct locations. To remedy these shortcomings we suggest model developments that will directly impact the ability of the SWMF to reproduce LGMDs, most importantly updating the ionospheric conductance calculation from empirical to physics-based.

79 ASTRONOMY AND ASTROPHYSICS↗