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NASA NTRS2014

A Spurious Jump in the Satellite Record: Has Antarctic Sea Ice Expansion Been Overestimated?

Recent estimates indicate that the Antarctic sea ice cover is expanding at a statistically significant rate with a magnitude one-third as large as the rapid rate of sea ice retreat in the Arctic. However, during the mid-2000s, with several fewer years in the observational record, the trend in Antarctic sea ice extent was reported to be considerably smaller and statistically indistinguishable from zero. Here, we show that much of the increase in the reported trend occurred due to the previously undocumented effect of a change in the way the satellite sea ice observations are processed for the widely used Bootstrap algorithm data set, rather than a physical increase in the rate of ice advance. Specifically, we find that a change in the intercalibration across a 1991 sensor transition when the data set was reprocessed in 2007 caused a substantial change in the long-term trend. Although our analysis does not definitively identify whether this change introduced an error or removed one, the resulting difference in the trends suggests that a substantial error exists in either the current data set or the version that was used prior to the mid- 2000s, and numerous studies that have relied on these observations should be reexamined to determine the sensitivity of their results to this change in the data set. Furthermore, a number of recent studies have investigated physical mechanisms for the observed expansion of the Antarctic sea ice cover. The results of this analysis raise the possibility that much of this expansion may be a spurious artifact of an error in the processing of the satellite observations.

Cryosphere↗

DOE OSTI2017

Micro-PIV measurements of multiphase flow of water and liquid CO 2 in 2-D heterogeneous porous micromodels

We present an experimental study of pore-scale flow dynamics of liquid CO 2 and water in a two-dimensional heterogeneous porous micromodel, inspired by the structure of a reservoir rock, at reservoir-relevant conditions (80 bar, 21°C). The entire process of CO 2 infiltration into a water-saturated micromodel was captured using fluorescence microscopy and the micro-PIV method, which together reveal complex fluid displacement patterns and abrupt changes in velocity. The CO 2 front migrated through the resident water in an intermittent manner, forming dendritic structures, termed fingers, in directions along, normal to, and even opposing the bulk pressure gradient. Such characteristics indicate the dominance of capillary fingering through the micromodel. Velocity burst events, termed Haines jumps, were also captured in the heterogeneous micromodel, during which the local Reynolds number was estimated to be ~21 in the CO 2 phase, exceeding the range of validity of Darcy's law. Furthermore, these drainage events were observed to be cooperative (i.e., across multiple pores simultaneously), with the zone of influence of such events extending beyond tens of pores, confirming, in a quantitative manner, that Haines jumps are nonlocal phenomena. After CO 2 completely breaks through the porous section, shear-induced circulations caused by flowing CO 2 were also observed, in agreement with previous studies using a homogeneous porous micromodel. To our knowledge, this study is the first quantitative measurement that incorporates both reservoir-relevant conditions and rock-inspired heterogeneity, and thus will be useful for pore-scale model development and validation.

42 ENGINEERING↗

NASA NTRS1977

Reliability analysis of forty-five strain-gage systems mounted on the first fan stage of a YF-100 engine

The reliability of 45 state-of-the-art strain gage systems under full scale engine testing was investigated. The flame spray process was used to install 23 systems on the first fan rotor of a YF-100 engine; the others were epoxy cemented. A total of 56 percent of the systems failed in 11 hours of engine operation. Flame spray system failures were primarily due to high gage resistance, probably caused by high stress levels. Epoxy system failures were principally erosion failures, but only on the concave side of the blade. Lead-wire failures between the blade-to-disk jump and the control room could not be analyzed.

Holanda, R.↗

NASA NTRS2006

Weather from the Stratosphere?

Is the stratosphere, the atmospheric layer between about 10 and 50 km, important for predicting changes in weather and climate? The traditional view is that the stratosphere is a passive recipient of energy and waves from weather systems in the underlying troposphere, but recent evidence suggests otherwise. At a workshop in Whistler, British Columbia (1), scientists met to discuss how the stratosphere responds to forcing from below, initiating feedback processes that in turn alter weather patterns in the troposphere. The lowest layer of the atmosphere, the troposphere, is highly dynamic and rich in water vapor, clouds, and weather. The stratosphere above it is less dense and less turbulent (see the figure). Variability in the stratosphere is dominated by hemispheric-scale changes in airflow on time scales of a week to several months. Occasionally, however, stratospheric air flow changes dramatically within just a day or two, with large-scale jumps in temperature of 20 K or more. The troposphere influences the stratosphere mainly through atmospheric waves that propagate upward. Recent evidence shows that the stratosphere organizes this chaotic wave forcing from below to create long-lived changes in the stratospheric circulation. These stratospheric changes can feed back to affect weather and climate in the troposphere.

Baldwin, Mark P.↗

NASA NTRS2015

Total Lightning Characteristics with Respect to Radar-Derived Mesocyclone Strength

Recent work investigating the microphysical and kinematic relationship between a storm's updraft, its total lightning production, and manifestations of severe weather has resulted in development of tools for improved nowcasting of storm intensity. The total lightning jump algorithm, which identifies rapid increases in total lightning flash rate that often precede severe events, has shown particular potential to benefit warning operations. Maximizing this capability of total lightning and its operational implementation via the lightning jump may best be done through its fusion with radar and radar‐derived intensity metrics. Identification of a mesocyclone, or quasi‐steady rotating updraft, in Doppler velocity is the predominant radar‐inferred early indicator of severe potential in a convective storm. Fused lightning‐radar tools that capitalize on the most robust intensity indicators would allow enhanced situational awareness for increased warning confidence. A foundational step toward such tools comes from a better understanding of the updraft‐centric relationship between intensification of total lightning production and mesocyclone development and strength. The work presented here utilizes a sample of supercell case studies representing a spectrum of severity. These storms are analyzed with respect to total lightning flash rate and the lightning jump alongside mesocyclone strength derived objectively from the National Severe Storms Laboratory (NSSL) Mesocyclone Detection Algorithm (MDA) and maximum azimuthal shear through a layer. Early results indicate that temporal similarities exist in the trends between total lightning flash rate and low‐ to mid‐level rotation in supercells. Other characteristics such as polarimetric signatures of rotation, flash size, and cloud‐to‐ground flash ratio are explored for added insight into the significance of these trends with respect to the updraft and related processes of severe weather production.

Stough, Sarah M.↗

DOE OSTI2016

Characterization of immiscible fluid displacement processes with various capillary numbers and viscosity ratios in 3D natural sandstone

We characterize the influence of reservoir conditions upon multiphase flow, we calculated fluid displacements (drainage processes) in 3D pore spaces of Berea sandstone using two-phase lattice Boltzmann (LB) simulations. The results of simulations under various conditions were used to classify the resulting two-phase flow behavior into three typical fluid displacement patterns on the diagram of capillary number (Ca) and viscosity ratio of the two fluids (M). In addition, the saturation of the nonwetting phase was calculated and mapped on the Ca–M diagram. We then characterized dynamic pore-filling events (i.e., Haines jumps) from the pressure variation of the nonwetting phase, and linked this behavior to the occurrence of capillary fingering. The results revealed the onset of capillary fingering in 3D natural rock at a higher Ca than in 2D homogeneous granular models, with the crossover region between typical displacement patterns broader than in the homogeneous granular model. Furthermore, saturation of the nonwetting phase mapped on the Ca–M diagram significantly depends on the rock models. These important differences between two-phase flow in 3D natural rock and in 2D homogeneous models could be due to the heterogeneity of pore geometry in the natural rock and differences in pore connectivity. By quantifying two-phase fluid behavior in the target reservoir rock under various conditions (e.g., saturation mapping on the Ca–M diagram), our approach could provide useful information for investigating suitable reservoir conditions for geo-fluid management (e.g., high CO 2 saturation in CO 2 storage).

58 GEOSCIENCES↗

DOE OSTI2019

Revealing Fast Structural Dynamics in pH-Responsive Peptides with Time-Resolved X-ray Scattering

Many biomaterials can adapt to changes in local biological environment (such as pH, temperature or ionic composition) in order to regulate function or deliver a payload. Such adaptation to environmental perturbation is typically a hierarchical process that begins with a response on a local structural level and then propagates to supramolecular and macromolecular scales. Understanding fast structural dynamics that occur upon the perturbation is important for rational design of functional biomaterials. However, few nanosecond time-resolved methods can probe both intra- and inter-molecular scales simultaneously with a high structural resolution. Here we utilize time-resolved x-ray scattering to probe nanosecond to microsecond structural dynamics of polypeptides undergoing protonation via a pH jump initiated by photoexcitation of a photoacid. Our results provide insight into the protonation-induced hierarchical changes in packing of peptide chains, formation of helical structure and associated collapse of the peptide chain.

Rimmerman, Dolev↗

NASA NTRS1995

Locomotion training of legged robots using hybrid machine learning techniques

In this study artificial neural networks and fuzzy logic are used to control the jumping behavior of a three-link uniped robot. The biped locomotion control problem is an increment of the uniped locomotion control. Study of legged locomotion dynamics indicates that a hierarchical controller is required to control the behavior of a legged robot. A structured control strategy is suggested which includes navigator, motion planner, biped coordinator and uniped controllers. A three-link uniped robot simulation is developed to be used as the plant. Neurocontrollers were trained both online and offline. In the case of on-line training, a reinforcement learning technique was used to train the neurocontroller to make the robot jump to a specified height. After several hundred iterations of training, the plant output achieved an accuracy of 7.4%. However, when jump distance and body angular momentum were also included in the control objectives, training time became impractically long. In the case of off-line training, a three-layered backpropagation (BP) network was first used with three inputs, three outputs and 15 to 40 hidden nodes. Pre-generated data were presented to the network with a learning rate as low as 0.003 in order to reach convergence. The low learning rate required for convergence resulted in a very slow training process which took weeks to learn 460 examples. After training, performance of the neurocontroller was rather poor. Consequently, the BP network was replaced by a Cerebeller Model Articulation Controller (CMAC) network. Subsequent experiments described in this document show that the CMAC network is more suitable to the solution of uniped locomotion control problems in terms of both learning efficiency and performance. A new approach is introduced in this report, viz., a self-organizing multiagent cerebeller model for fuzzy-neural control of uniped locomotion is suggested to improve training efficiency. This is currently being evaluated for a possible patent by NASA, Johnson Space Center. An alternative modular approach is also developed which uses separate controllers for each stage of the running stride. A self-organizing fuzzy-neural controller controls the height, distance and angular momentum of the stride. A CMAC-based controller controls the movement of the leg from the time the foot leaves the ground to the time of landing. Because the leg joints are controlled at each time step during flight, movement is smooth and obstacles can be avoided. Initial results indicate that this approach can yield fast, accurate results.

Simon, William E.↗

DOE OSTI2024

Numerical analysis of coalescence-induced bubble departure for enhanced boiling heat transfer

Boiling heat transfer plays a crucial role in a wide range of applications, such as power generation, refrigeration, electronics cooling, and pharmaceutics. Among the various factors that influence boiling heat transfer, the dynamics of vapor bubble nucleation, growth, and departure from the heated surface stand out as particularly important. An emerging phenomenon that can promote the departure of bubbles smaller than the Fritz diameter is coalescence-induced departure. If the dynamics of this process are fully understood, then surfaces can be engineered to promote faster bubble departure and substantially increase the performance of boiling heat transfer. Further, this work expands on published results by presenting a detailed numerical analysis of bubble coalescence and departure for a range of initial bubble diameters and size ratios between coalescing bubbles. Analysis of the results is focused on explaining how the release of surface energy and bubble surface dynamics lead to bubble departure, as well as fundamentally distinguishing capillary–inertial jumping and buoyant–inertial departure mechanisms across different bubble sizes and size ratios. The results show that both the initial sizes of the coalescing bubbles and the ratio between their sizes can determine whether the merged bubble will leave the surface through capillary–inertial jumping or buoyant departure. Below a certain bubble size, the release of surface energy by the merger is not sufficient to propel the merged bubble from the surface.

42 ENGINEERING↗

NASA NTRS1993

Ion and electron heating at the low-Mach-number, quasi-parallel bow shock

The study examines the magnetic structure and energy dissipation at low-Mach-number, quasi-parallel collisionless shocks on the basis of observations obtained by the ISEE 1 and 2 spacecraft at seven crossings of the earth's dayside bow shock. All the shocks exhibit a fairly short-scale-length ramp where the principal jumps in the electron temperature, ion temperature, and magnetic field strength take place. Large-amplitude LF transverse waves in the magnetic field are present in and downstream from the ramp, with more modest waves upstream. The amplitude of the downstream waves is typically larger than can be accounted for by shock compression of the upstream waves. The electron heating represents about 6 percent of the dissipated bulk flow energy, consistent with observations in other parameter regimes, and suggesting that the dominant electron heating process is the same. It is suggested that the low-Mach-number shocks are reforming but do not exhibit downstream variability because of the relatively low levels of reflected ions.

Thomsen, M. F.↗

NASA NTRS1994

Towards a Modern Theory of Multiphase Filtration Flow

An alternative theoretical model of joint filtration flow of immiscible incompressible fluids is presented. The model takes into account relaxation processes due to the interchange of the fluids between pores of difference sizes which is driven by capillary forces. The fluids occupy connected regions in a four-dimensional space formed by three coordinates and the pore length scale. When the fluid exchange between pores of given sizes is effected by way of successive flow through pores of all the intermediate sizes, the pressure within each region is governed by a hyperbolic equation, the role of time being played by the pore linear scale. Pressure jumps across hypersurfaces separating the regions equal corresponding values of the capillary pressure. A supplementary condition at any such hypersurface requires the speed of its displacement in the four-dimensional space to coincide with the normal velocity components of both the adjoining fluids. As a result, a principally new statement of multiphase filtration flow problems is gained with allowance for capillary relaxation in the porous space.

Buyevich, Yu A.↗

NASA NTRS1990

Nonlinear dynamics of global atmospheric and Earth-system processes

Researchers are continuing their studies of the nonlinear dynamics of global weather systems. Sensitivity analyses of large-scale dynamical models of the atmosphere (i.e., general circulation models i.e., GCM's) were performed to establish the role of satellite-signatures of soil moisture, sea surface temperature, snow cover, and sea ice as crucial boundary conditions determining global weather variability. To complete their study of the bimodality of the planetary wave states, they are using the dynamical systems approach to construct a low-order theoretical explanation of this phenomenon. This work should have important implications for extended range forecasting of low-frequency oscillations, elucidating the mechanisms for the transitions between the two wave modes. Researchers are using the methods of jump analysis and attractor dimension analysis to examine the long-term satellite records of significant variables (e.g., long wave radiation, and cloud amount), to explore the nature of mode transitions in the atmosphere, and to determine the minimum number of equations needed to describe the main weather variations with a low-order dynamical system. Where feasible they will continue to explore the applicability of the methods of complex dynamical systems analysis to the study of the global earth-system from an integrative viewpoint involving the roles of geochemical cycling and the interactive behavior of the atmosphere, hydrosphere, and biosphere.

Saltzman, Barry↗

DOE OSTI2024

Neural network kinetics for exploring diffusion multiplicity and chemical ordering in compositionally complex materials

Diffusion involving atom transport from one location to another governs many important processes and behaviors such as precipitation and phase nucleation. The inherent chemical complexity in compositionally complex materials poses challenges for modeling atomic diffusion and the resulting formation of chemically ordered structures. Here, we introduce a neural network kinetics (NNK) scheme that predicts and simulates diffusion-induced chemical and structural evolution in complex concentrated chemical environments. The framework is grounded on efficient on-lattice structure and chemistry representation combined with artificial neural networks, enabling precise prediction of all path-dependent migration barriers and individual atom jumps. To demonstrate the method, we study the temperature-dependent local chemical ordering in a refractory NbMoTa alloy and reveal a critical temperature at which the B2 order reaches a maximum. The atomic jump randomness map exhibits the highest diffusion heterogeneity (multiplicity) in the vicinity of this characteristic temperature, which is closely related to chemical ordering and B2 structure formation. The scalable NNK framework provides a promising new avenue to exploring diffusion-related properties in the vast compositional space within which extraordinary properties are hidden.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Plasma Treated Active Carbon for Capacitive Deionization of Saline Water

The plasma treatment on commercial active carbon (AC) was carried out in a capacitively coupled plasma system using Ar + 10% O 2 at pressure of 4.0 Torr. The RF plasma power ranged from 50 W to 100 W and the processing time was 10 min. The carbon film electrode was fabricated by electrophoretic deposition. Micro-Raman spectroscopy revealed the highly increased disorder of sp 2 C lattice for the AC treated at 75 W. An electrosorption capacity of 6.15 mg/g was recorded for the carbon treated at 75 W in a 0.1 mM NaCl solution when 1.5 V was applied for 5 hours, while the capacity of the untreated AC was 1.0 mg/g. The plasma treatment led to 5.09 times increase in the absorption capacity. The jump of electrosorption capacity by plasma treatment was consistent with the Raman spectra and electrochemical double layer capacitance. This work demonstrated that plasma treatment was a potentially efficient approach to activating biochar to serve as electrode material for capacitive deionization (CDI).

36 MATERIALS SCIENCE↗

DOE OSTI2018

A hybrid origin of the Martian crustal dichotomy: Degree-1 convection antipodal to a giant impact

The Martian crustal dichotomy is the stark ~5 km difference in surface elevation and ~26 km difference in crustal thickness between the northern lowlands and southern highlands that originated within 100s of Myr of Mars’ formation. The origin of the dichotomy has broad implications for the geodynamic history of Mars, but purely exogenic or endogenic theories so far cannot explain all of the large scale geophysical observations associated with dichotomy formation. A giant impact can produce the shape and slope of the dichotomy boundary, but struggles to explain Mars’ remanent crustal magnetic signatures and the ultimate formation of Tharsis. Degree-1 mantle convection can relate the crustal dichotomy to the formation of Tharsis, but does not explain the elliptical dichotomy shape and must be initiated by a large pre-existing viscosity jump in the mantle. We propose a hybrid model of dichotomy formation in which a giant impact induces degree-1 convection with an upwelling antipodal to the impact site. In this scenario, a giant impact in the northern hemisphere excavates crust, creating an initial difference in crustal thickness and possibly composition between the two hemispheres. Over 10s to 100s of Myr, the dominant upwelling(s) would migrate to be under the thicker, insulating crust in the southern hemisphere, generating melt that further thickens the southern crust. We examine this process using 3-D mantle convection simulations, and find that a hemispherical difference in crustal thickness and composition caused by a giant impact can induce degree-1 convection with the upwelling(s) antipodal to the impact site in <100 Myr.

58 GEOSCIENCES↗

NASA NTRS1997

Effects of Bioreactor Retention Time on Aerobic Microbial Decomposition of CELSS Crop Residues

The focus of resource recovery research at the KSC-CELSS Breadboard Project has been the evaluation of microbiologically mediated biodegradation of crop residues by manipulation of bioreactor process and environmental variables. We will present results from over 3 years of studies that used laboratory- and breadboard-scale (8 and 120 L working volumes, respectively) aerobic, fed-batch, continuous stirred tank reactors (CSTR) for recovery of carbon and minerals from breadboard grown wheat and white potato residues. The paper will focus on the effects of a key process variable, bioreactor retention time, on response variables indicative of bioreactor performance. The goal is to determine the shortest retention time that is feasible for processing CELSS crop residues, thereby reducing bioreactor volume and weight requirements. Pushing the lower limits of bioreactor retention times will provide useful data for engineers who need to compare biological and physicochemical components. Bioreactor retention times were manipulated to range between 0.25 and 48 days. Results indicate that increases in retention time lead to a 4-fold increase in crop residue biodegradation, as measured by both dry weight losses and CO2 production. A similar overall trend was also observed for crop residue fiber (cellulose and hemicellulose), with a noticeable jump in cellulose degradation between the 5.3 day and 10.7 day retention times. Water-soluble organic compounds (measured as soluble TOC) were appreciably reduced by more than 4-fold at all retention times tested. Results from a study of even shorter retention times (down to 0.25 days), in progress, will also be presented.

Strayer, R. F.↗

DOE OSTI2021

Phenomenon Identification and Ranking Table Development for Future Application Figure-of-Merit Studies on Thermal Energy Storage Integrations with Light Water Reactors

There are no standard prioritization criteria for evaluating thermal energy storage (TES) options for use in integrated energy systems. A framework for proposing, analyzing, and presenting energy storage integration with power producers and users is presented along with a specific figure-of-merit (FOM) study based in this framework. This basis for evaluating storage technologies can provide a structure for the energy industry to analyze and prioritize energy storage in different applications and environments. The phenomena identification and ranking table (PIRT) presents a series of design questions specific to energy storage applications. The FOM study, built in this PIRT framework based on a nuclear-renewable hybrid energy system using TES to produce power and provide process energy for a secondary user, successfully identified specific technologies to use based on the project requirements. Expanding the library of projects using this framework will expand the deployable options for energy storage and increase its potential for energy security.

25 ENERGY STORAGE↗

DOE OSTI2025

Assessing the difficulty of capturing the distribution function of neutrinos in neutron star merger simulations

The collision of two neutron stars is a rich source of information about nuclear physics. In particular, the kilonova signal following a merger can help us elucidate the role of neutron stars in nucleosynthesis, and informs us about the properties of matter above nuclear saturation. Approximate modeling of neutrinos remains an important limitation to our ability to make predictions for these observables. Part of the problem is the fermionic nature of neutrinos. By the exclusion principle, the expected value 𝑓 𝜈 for the number of neutrinos in a quantum state is at most 1. Any process producing neutrinos is suppressed by a blocking factor (1 −𝑓 𝜈 ). Recent simulations focused on neutrino physics mostly use a gray two-moment scheme to evolve neutrinos. This evolves integrals of 𝑓 𝜈 over momentum space, preventing direct calculations of blocking factors. Monte Carlo methods may be an attractive alternative, providing access to the full distribution of neutrinos. Their current implementation is, however, inadequate to estimate 𝑓 𝜈 : in our most recent simulations, a single Monte Carlo packet causes, in the worst cases, estimates of 𝑓 𝜈 to jump from 𝑓 𝜈 =0 to 𝑓 𝜈 ∼10 5 . While this is concerning, this brazen violation of the fermionic nature of neutrinos has been largely inconsequential, as the interactions used in simulations avoid direct calculations of 𝑓 𝜈 . We are, however, reaching a level of modeling at which this problem can no longer be ignored. Here, we discuss the relatively simple origin of this issue. We then show that very rough estimates of 𝑓 𝜈 can in theory be obtained in merger simulations, but that they will require a combination of unintuitive weighting schemes for Monte Carlo packets and smoothing of the neutrino distribution at coarser resolution than what the merger simulation uses.

79 ASTRONOMY AND ASTROPHYSICS↗