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At least 1,369 records · Page 76

On the negative polarization of light scattered by subwavelength regolithic grains

Recent laboratory polarimetric measurements of light scattering by layers of alumina grains of different size are used to examine the relevance of the Wolff & Dollfus (1990) theory of negative polarization, which has been developed to describe light scattering by regolithic grains of arbitrary size. It is demonstrated that, while reproducing satisfactorily the main polarization characteristics of light scattering by grains much greater than the wavelength, this theory does not describe the negative polarization of light measured by Geake & Geake (1990) for subwavelength-sized grains. The smallest grains exhibit a polarization feature that may be called the 'polarization opposition effect'. This feature requires an alternative explanation and may be due to the so-called weak localization of photons in discrete random media.

Kolokolova, L. O.↗

Effect of Fiber Orientation on Ball Failures Under Rolling-contact Conditions

The rolling-contact fatigue spin rig was used to test bails of a bearing steel at maximum Hertz stresses of 600,000 to 750,000 psi. The effect of fiber orientation was observed with the ball track restricted to passing directly over the poles, coincident with the equator, or randomly around the ball. The polar areas were found to be weaker in fatigue than the nonpolar areas. This resulted in a much greater portion of the failures occurring in the polar areas than would be expected from a homogeneous material. The early failures are discussed.

MATERIALS, PROPERTIES - FATIGUE↗

Postural Effects on Intracranial Pressure as Assessed Noninvasively

This study was designed to investigate effects of whole body tilting on intracranial compliance and pressure in six healthy volunteers by using a noninvasive ultrasonic device. Subjects were randomly tilted up or down sequentially at 60 degree, 30 degree head-up, supine, and 15 degree head-down position for one minute at each angle. We measured arterial blood pressure with a finger pressure cuff and changes in intracranial distance with an ultrasonic device. The device measures skull movement on the order of micro-meter. Our ultrasound technique demonstrates that skull movement is highly correlated (r$(circumflex){2}$=0.77) with intracranial pressure variations due to cerebral arterial pulsation. The amplitudes of arterial pressure (r$(circumflex){2}$=0.99 and those of intracranial distance changes (r$(circumflex){2}$=0.87) associated with one cardiac cycle were inversely correlated with the angle of tilt. The ratio of pulsation amplitudes for intracranial distance over arterial pressure also showed a significant increase as the angle of tilt was lowered (p=0.003). Thus, postural changes alter intracranial compliance in healthy volunteers and intracranial volume-buffering capacity is reduced in head-down position.

Ueno, Toshiaki↗

Semiconductor Crystal Growth in Static and Rotating Magnetic fields

Magnetic fields have been applied during the growth of bulk semiconductor crystals to control the convective flow behavior of the melt. A static magnetic field established Lorentz forces which tend to reduce the convective intensity in the melt. At sufficiently high magnetic field strengths, a boundary layer is established ahead of the solid-liquid interface where mass transport is dominated by diffusion. This can have a significant effect on segregation behavior and can eliminate striations in grown crystals resulting from convective instabilities. Experiments on dilute (Ge:Ga) and solid solution (Ge-Si) semiconductor systems show a transition from a completely mixed convective state to a diffusion-controlled state between 0 and 5 Tesla. In HgCdTe, radial segregation approached the diffusion limited regime and the curvature of the solid-liquid interface was reduced by a factor of 3 during growth in magnetic fields in excess of 0.5 Tesla. Convection can also be controlled during growth at reduced gravitational levels. However, the direction of the residual steady-state acceleration vector can compromise this effect if it cannot be controlled. A magnetic field in reduced gravity can suppress disturbances caused by residual transverse accelerations and by random non-steady accelerations. Indeed, a joint program between NASA and the NHMFL resulted in the construction of a prototype spaceflight magnet for crystal growth applications. An alternative to the suppression of convection by static magnetic fields and reduced gravity is the imposition of controlled steady flow generated by rotating magnetic fields (RMF)'s. The potential benefits of an RMF include homogenization of the melt temperature and concentration distribution, and control of the solid-liquid interface shape. Adjusting the strength and frequency of the applied magnetic field allows tailoring of the resultant flow field. A limitation of RMF's is that they introduce deleterious instabilities above a critical magnetic field value. Growth conditions in which static magnetic fields rotational magnetic fields, and reduced gravitational levels can have a beneficial role will be described.

Volz, Martin↗

Vibration damping of the Cassini spacecraft structure

Cassini is a large robotic spacecraft currently under development at the Jet Propulsion Laboratory (JPL) whose interplanetary scientific mission is to explore Saturn, its ring, and its moons. Cassini is scheduled to launch on a Titan IV rocket with a Centaur upper stage booster, and will be protected during ascent through the atmosphere by a lightweight aluminum payload fairing (PLF). As a result of the extreme noise levels generated by the powerful Titan IV at liftoff, and the acoustic transparency of the PLF, Cassini is predicted to experience sever acoustic levels. Furthermore, the high acoustic levels, coupled with the size and configuration of the spacecraft, will induce unacceptable random vibration levels on the structure and critical spacecraft components. Studies showed that the use of Tuned Vibration Absorbers (TVAs) would be effective in reducing vibration. A series of reverberant acoustic tests were performed on a partial development test model (DTM) of Cassini to evaluate the effectiveness of TVAs in reducing the structural vibration. The test results showed that significant vibration attenuation was achieved.

vibration damping↗

How hydrophobicity, side chains, and salt affect the dimensions of disordered proteins

Abstract Despite the generally accepted role of the hydrophobic effect as the driving force for folding, many intrinsically disordered proteins (IDPs), including those with hydrophobic content typical of foldable proteins, behave nearly as self‐avoiding random walks (SARWs) under physiological conditions. Here, we tested how temperature and ionic conditions influence the dimensions of the N‐terminal domain of pertactin (PNt), an IDP with an amino acid composition typical of folded proteins. While PNt contracts somewhat with temperature, it nevertheless remains expanded over 10–58°C, with a Flory exponent, ν , >0.50. Both low and high ionic strength also produce contraction in PNt, but this contraction is mitigated by reducing charge segregation. With 46% glycine and low hydrophobicity, the reduced form of snow flea anti‐freeze protein (red‐sfAFP) is unaffected by temperature and ionic strength and persists as a near‐SARW, ν ~ 0.54, arguing that the thermal contraction of PNt is due to stronger interactions between hydrophobic side chains. Additionally, red‐sfAFP is a proxy for the polypeptide backbone, which has been thought to collapse in water. Increasing the glycine segregation in red‐sfAFP had minimal effect on ν . Water remained a good solvent even with 21 consecutive glycine residues ( ν > 0.5), and red‐sfAFP variants lacked stable backbone hydrogen bonds according to hydrogen exchange. Similarly, changing glycine segregation has little impact on ν in other glycine‐rich proteins. These findings underscore the generality that many disordered states can be expanded and unstructured, and that the hydrophobic effect alone is insufficient to drive significant chain collapse for typical protein sequences.

59 BASIC BIOLOGICAL SCIENCES↗

TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations

TURBOMOLE is a collaborative, multi-national software development project aiming to provide highly efficient and stable computational tools for quantum chemical simulations of molecules, clusters, periodic systems, and solutions. The TURBOMOLE software suite is optimized for widely available, inexpensive, and resource-efficient hardware such as multi-core workstations and small computer clusters. TURBOMOLE specializes in electronic structure methods with outstanding accuracy–cost ratio, such as density functional theory including local hybrids and the random phase approximation (RPA), GW-Bethe–Salpeter methods, second-order Møller–Plesset theory, and explicitly correlated coupled-cluster methods. TURBOMOLE is based on Gaussian basis sets and has been pivotal for the development of many fast and low-scaling algorithms in the past three decades, such as integral-direct methods, fast multipole methods, the resolution-of-the-identity approximation, imaginary frequency integration, Laplace transform, and pair natural orbital methods. This review focuses on recent additions to TURBOMOLE’s functionality, including excited-state methods, RPA and Green’s function methods, relativistic approaches, high-order molecular properties, solvation effects, and periodic systems. A variety of illustrative applications along with accuracy and timing data are discussed. Moreover, available interfaces to users as well as other software are summarized. TURBOMOLE’s current licensing, distribution, and support model are discussed, and an overview of TURBOMOLE’s development workflow is provided. Challenges such as communication and outreach, software infrastructure, and funding are highlighted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integrating Experiments and Well Logs to Predict Caney Shale Static Mechanical Properties During Production with Supervised Machine Learning

Caney shale is one of the emerging oil reservoirs in Oklahoma. Understanding the impact of effective stress on its mechanical properties is critical for predicting hydraulic fracture geometry and overall hydrocarbon production. The objective of our study is to evaluate the impact of effective stress on the dynamic Young’s modulus using ultrasonic velocity measurements for Caney shale samples. A triaxial cell was utilized to measure ultrasonic (P-wave and S-wave) velocities for ten downhole Caney shale samples under various effective stresses to indirectly assess the impact of pore pressure change. The dynamic Young’s moduli estimated from these measurements were integrated with available conventional well logs (excluding sonic logs) and triaxial test results from Benge et al. (2021) to predict the static Young’s modulus using Random Forest (RF) and Extreme Gradient Boosting (XGBoost) models. The results showed that the estimated dynamic Young’s moduli from ultrasonic measurements were higher than the corresponding static Young’s modulus of cores from the same vertical well at similar depths. With increasing effective stress, the dynamic Young’s modulus increased for all samples. The estimated dynamic-to-static correction factor tended to be higher in zones of high neutron porosity (PHIN) and low density compared to other zones. Finally, SHapley Additive exPlanations (SHAP) for RF and XGBoost models identified depth, gamma ray (GR), and PHIN as key features for predicting the static Young’s modulus. This study enhances our understanding of the dynamic and static Young’s moduli for the Caney shale interval, as a function of effective stress and conventional well logs. The findings from this study can improve predictions of production throughout the well's lifespan by offering insights into the mechanical property degradation resulting from pore pressure depletion.

Kholy, Sherif M.↗

Improved methods for the measurement and analysis of stellar magnetic fields

The paper presents several improved methods for the measurement of magnetic fields on cool stars which take into account simple radiative transfer effects and the exact Zeeman patterns. Using these methods, high-resolution, low-noise data can be fitted with theoretical line profiles to determine the mean magnetic field strength in stellar active regions and a model-dependent fraction of the stellar surface (filling factor) covered by these regions. Random errors in the derived field strength and filling factor are parameterized in terms of signal-to-noise ratio, wavelength, spectral resolution, stellar rotation rate, and the magnetic parameters themselves. Weak line blends, if left uncorrected, can have significant systematic effects on the derived magnetic parameters, and thus several methods are developed to compensate partially for them. The magnetic parameters determined by previous methods likely have systematic errors because of such line blends and because of line saturation effects. Other sources of systematic error are explored in detail. These sources of error currently make it difficult to determine the magnetic parameters of individual stars to better than about + or - 20 percent.

Saar, Steven H.↗

Ab initio property predictions of quinary solid solutions using small binary cells

The Set of Small Ordered Structures (SSOS) approach is an ab initio technique for modelling random solid solutions in which many small structures are averaged so that their correlation functions match those of a desired composition. SSOS has been shown to be effective in reducing the cost of density functional theory calculations relative to other well-known techniques such as cluster expansions and special quasirandom structures for modelling solid solutions. Here in this work, we demonstrate that SSOS’s can be constructed using cells with only a subset of elements while still accurately modelling multi-component systems. Specifically, we show that small binary cells can effectively model two quinary high entropy alloys – NbTaTiHfZr and MoNbTaVW – accurately capturing properties such as formation energy, lattice parameters, elastic constants, and root-mean-square atomic displacements. Overall, this insight is useful for those looking to construct databases of such small structures for predicting the properties of multi-component solid solutions, as it greatly decreases the number of structures that needs to be considered.

36 MATERIALS SCIENCE↗

Effects of Resonance in Quasi-Periodic Oscillators of Neutron Star Binaries

Using a large quantity of Rossi X-Ray Timing Explorer data presented in the literature, I offer a detailed investigation into the accuracy of the quasi-periodic oscillation (QPO) frequency determination. The QPO phenomenon seen in X-ray binaries is possibly a result of the resonance of the intrinsic (eigen) oscillations and harmonic driving forces of the system. I show that the resonances, in the presence of the damping of oscillations, occur at frequencies that are systematically and randomly shifted with respect to the eigenfrequencies of the system. The shift value strongly depends on the damping rate that is measured by the half-width of the QPO feature. Taking into account this effect, I analyze the QPO data for four Z sources, Scorpius X-I, GX 340+0, GX 5-1, and GX 17+2, and two atoll sources, 4U 1728-34 and 4U 0614+09. The transition-layer model (TLM) predicts the existence of the invariant quantity delta, an inclination angle of the magnetospheric axis with respect to the normal to the disk. I calculate delta and the error bars of delta using the resonance shift, and I find that the inferred delta-values are consistent with constants for these four Z sources, in which horizontal-branch oscillation and kilohertz frequencies have been detected and correctly identified. It is shown that the inferred delta are in the range between 5.5 deg and 6.5 deg. I conclude that the TLM seems to be compatible with the data.

Titarchuk, Lev↗

Consumer safety-oriented scheduling of rotating power outages during heat waves

Extreme heat events have widespread effects on power systems, reducing available generation capacity, limiting transmission capabilities, and causing unusual demand patterns on the consumer side. As these combined effects expose bulk transmission systems to potential large-scale blackouts, utilities may be required to schedule and apply rotating outages, by temporarily and alternately disconnecting distribution substations to reduce overload. However, utilities lack mechanisms to inform these events, exacerbating the negative effects of heat waves on affected communities. This paper introduces a novel framework for scheduling rotating outages during heat waves while considering impacts on consumers’ safety. Instead of random sequential load shedding, we propose a methodology to rotate power outages considering a metric that quantifies the indoor overheating risk of groups of consumers during a power outage. The overheating risk is derived from a detailed building simulation using CityBES, where the buildings are modeled based on available data—use type, year built, floor area, number of stories, location—while presence of air conditioning and occupancy are calibrated from smart meter data. Based on the metric, an algorithm to schedule the rotating outages is applied to prioritize feeders for disconnection at each hour according to their overheating risk to meet a utility load reduction target. Applied to two substations and seven feeders in the Portland General Electric territory, the results show that this approach effectively leads to the lowest overheating risk during the resulting outage schedules, with an average 10.1% lower overheating compared to uninformed schedules.

Building thermal simulation↗

Compositional patterning in irradiated alloys: Effective potentials and effective interfacial energy

Compositional patterning (CP) in binary alloys during energetic particle irradiation is studied using a kinetic model that considers two competing kinetic processes, a thermally activated one promoting macroscopic phase separation (MPS) of the concentration field c(r,t) and a forced one resulting in finite-range random atomic mixing. The forced mixing is modeled by a Gaussian relocation distribution with a characteristic distance R. A series of approximate kinetic models are introduced by expanding the mixing function into a series of n terms, thus replacing the non-local evaluations of the concentration field c(r'-r,t) by local derivatives of c(r,t). This approach makes it possible to obtain exact effective potentials and build steady-state diagrams for each order-n model. Phase field (PF) simulations using these order-n models reveal that near the onset of patterning, phase evolution is accurately described using an order-3 model, which changes smoothly from an extended Cahn-Hilliard free energy in the MPS regime to a one-mode Swift-Hohenberg functional in the CP regime. Deeper into the patterning regime, higher-order models are required to achieve convergence, yielding square-like concentration profiles characteristic of a strong segregation regime. These higher-order effective free energies are analogous to multimodal Swift-Hohenberg functionals. Here, a new definition for the effective interfacial energy is proposed in the CP regime, since the interfacial area is no longer an excess quantity in that regime, precluding the use of the standard thermodynamic definition of interfacial energy.

36 MATERIALS SCIENCE↗

Modeled and observed properties related to the direct aerosol radiative effect of biomass burning aerosol over the southeastern Atlantic

Biomass burning smoke is advected over the southeastern Atlantic Ocean between July and October of each year. This smoke plume overlies and mixes into a region of persistent low marine clouds. Model calculations of climate forcing by this plume vary significantly in both magnitude and sign. NASA EVS-2 (Earth Venture Suborbital-2) ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) had deployments for field campaigns off the west coast of Africa in 3 consecutive years (September 2016, August 2017, and October 2018) with the goal of better characterizing this plume as a function of the monthly evolution by measuring the parameters necessary to calculate the direct aerosol radiative effect. Here, this dataset and satellite retrievals of cloud properties are used to test the representation of the smoke plume and the underlying cloud layer in two regional models (WRF-CAM5 and CNRM-ALADIN) and two global models (GEOS and UM-UKCA). The focus is on the comparisons of those aerosol and cloud properties that are the primary determinants of the direct aerosol radiative effect and on the vertical distribution of the plume and its properties. The representativeness of the observations to monthly averages are tested for each field campaign, with the sampled mean aerosol light extinction generally found to be within 20 % of the monthly mean at plume altitudes. When compared to the observations, in all models, the simulated plume is too vertically diffuse and has smaller vertical gradients, and in two of the models (GEOS and UM-UKCA), the plume core is displaced lower than in the observations. Plume carbon monoxide, black carbon, and organic aerosol masses indicate underestimates in modeled plume concentrations, leading, in general, to underestimates in mid-visible aerosol extinction and optical depth. Biases in mid-visible single scatter albedo are both positive and negative across the models. Observed vertical gradients in single scatter albedo are not captured by the models, but the models do capture the coarse temporal evolution, correctly simulating higher values in October (2018) than in August (2017) and September (2016). Uncertainties in the measured absorption Ångstrom exponent were large but propagate into a negligible (<4 %) uncertainty in integrated solar absorption by the aerosol and, therefore, in the aerosol direct radiative effect. Model biases in cloud fraction, and, therefore, the scene albedo below the plume, vary significantly across the four models. The optical thickness of clouds is, on average, well simulated in the WRF-CAM5 and ALADIN models in the stratocumulus region and is underestimated in the GEOS model; UM-UKCA simulates cloud optical thickness that is significantly too high. Overall, the study demonstrates the utility of repeated, semi-random sampling across multiple years that can give insights into model biases and how these biases affect modeled climate forcing. The combined impact of these aerosol and cloud biases on the direct aerosol radiative effect (DARE) is estimated using a first-order approximation for a subset of five comparison grid boxes. A significant finding is that the observed grid box average aerosol and cloud properties yield a positive (warming) aerosol direct radiative effect for all five grid boxes, whereas DARE using the grid-box-averaged modeled properties ranges from much larger positive values to small, negative values. It is shown quantitatively how model biases can offset each other, so that model improvements that reduce biases in only one property (e.g., single scatter albedo but not cloud fraction) would lead to even greater biases in DARE. Across the models, biases in aerosol extinction and in cloud fraction and optical depth contribute the largest biases in DARE, with aerosol single scatter albedo also making a significant contribution.

54 ENVIRONMENTAL SCIENCES↗

Quantum Embedding Theory for Strongly Correlated States in Materials

Quantum embedding theories are promising approaches to investigate strongly correlated electronic states of active regions of large-scale molecular or condensed systems. Notable examples are spin defects in semiconductors and insulators. We present a detailed derivation of a quantum embedding theory recently introduced, which is based on the definition of effective Hamiltonians. The effect of the environment on a chosen active space is accounted for through screened Coulomb interactions evaluated using density functional theory. Importantly, the random phase approximation is not required, and the evaluation of virtual electronic orbitals is circumvented with algorithms previously developed in the context of calculations based on many-body perturbation theory. In addition, we generalize the quantum embedding theory to active spaces composed of orbitals that are not eigenstates of Kohn–Sham Hamiltonians. Finally, we report results for spin defects in semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nucleon-induced inelastic scattering with statistical strength functions and the ECIS direct reaction code

Modern theoretical descriptions of inelastic scattering make use of multi-step direct reaction approaches together with transition potentials obtained from sophisticated nuclear structure models. Here we demonstrate how the complexity of such calculations can be reduced to permit simpler ones, also using the ECIS code, but providing an almost equally precise alternative to a much more detailed calculation. We have studied the transition form factors within the random phase approximation (RPA), where these are obtained as linear combinations of particle–hole states. At moderate to high excitation energies, where interference effects tend to disappear, we have proposed an independent particle–hole formalism in which particle–hole states are spread in energy with an appropriate strength function obtained from the RPA. The effects of more complex modes, such as 2p–2h ones, are simulated with widths calculated in a semi-classical context. In this work, we verify the validity of our approximations for pre-equilibrium proton-induced reactions on 90 Zr target. Our calculations provide a good description of the reaction data and point toward a simplification of the description of nucleon-induced reactions based on averages of microscopic details of the projectile–target interaction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Stochastic mean-field theory and applications to multinucleon transfer and kinetic energy dissipation processes in heavy-ion collisions

In this Review article, a brief description of the stochastic mean-field (SMF) theory for describing reaction dynamics in low-energy heavy-ion collisions at bombarding energies in the vicinity of the Coulomb barrier is presented. In these collisions, as a result of strong Pauli blocking, binary nucleon collisions do not have a significant effect on the dissipation and fluctuations. At low energies, the mean-field fluctuations, due to initial correlations, have a dominant effect on fluctuations of macroscopic variables. The SMF theory proposes the determination of an ensemble of single-particle density matrices by specifying random initial fluctuations according to a distribution law. Employing an ensemble of single-particle density matrices, not only the mean values but also the distribution functions of the one-body observables can be determined. If the di-nuclear structure is maintained in heavy-ion collisions, such as deep inelastic collisions and fast quasi-fission reactions, a much simpler description of the reaction mechanism can be derived in terms of several macroscopic variables such as mass and charge asymmetry, and relative linear and relative angular momentum. In this case, by geometric projection of the SMF equations, it is possible to derive the quantal Langevin equations for macroscopic variables. As an application of quantal transport description, an analysis of multinucleon transfers and kinetic energy dissipation and fluctuations is presented for selected quasi-fission reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Primary separation between three aircraft using traffic displays

The use of a sophisticated traffic and map display termed electronic flight rules (EFR) by general aviation pilots for primary seperation in low density airspace is studied. The experimental flights were made under four conditions: with and without sensor noise in the traffic information and with and without communications for traffic coordination. Pilots were required to maintain two miles horizontal and 500 ft vertical separation from other aircraft for 24 different traffic situations repeated randomly for each of the four experimental conditions. Of 1152 aircraft encounters 12.8 percent were in violation of separation minimums. In general, the effects of sensor noise were minimal, communications affected some of the measures, and the group effect was quite significant. When pilots were able to communicate and coordinate their maneuvers, the time to resolve conflict was reduced.

Chappell, S. L.↗