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At least 415 records · Page 23

Quantum theory of three-dimensional de Sitter space

We sketch the construction of a quantum model of three-dimensional de Sitter space, based on the covariant entropy principle and the observation that semiclassical physics suggests the possibility of a consistent theory of a finite number of unstable massive particles with purely gravitational interactions. Our model is holographic, finite, unitary, causal, plausibly exhibits fast scrambling, and qualitatively reproduces features of semiclassical de Sitter physics. In an appendix we outline some calculations that might lead to further tests of the model. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Using diverse potentials and scoring functions for the development of improved machine-learned models for protein–ligand affinity and docking pose prediction

The advent of computational drug discovery holds the promise of significantly reducing the effort of experimentalists, along with monetary cost. More generally, predicting the binding of small organic molecules to biological macromolecules has far-reaching implications for a range of problems, including metabolomics. However, problems such as predicting the bound structure of a protein–ligand complex along with its affinity have proven to be an enormous challenge. In recent years, machine learning-based methods have proven to be more accurate than older methods, many based on simple linear regression. Nonetheless, there remains room for improvement, as these methods are often trained on a small set of features, with a single functional form for any given physical effect, and often with little mention of the rationale behind choosing one functional form over another. Moreover, it is not entirely clear why one machine learning method is favored over another. Here, we endeavor to undertake a comprehensive effort towards developing high-accuracy, machine-learned scoring functions, systematically investigating the effects of machine learning method and choice of features, and, when possible, providing insights into the relevant physics using methods that assess feature importance. Here, we show synergism among disparate features, yielding adjusted R 2 with experimental binding affinities of up to 0.871 on an independent test set and enrichment for native bound structures of up to 0.913. When purely physical terms that model enthalpic and entropic effects are used in the training, we use feature importance assessments to probe the relevant physics and hopefully guide future investigators working on this and other computational chemistry problems.

59 BASIC BIOLOGICAL SCIENCES↗

The Fast Alternative Cryogenic Experiment Testbed

One of the challenges in the area of cryogenics for space exploration in the next millennium is providing the capability for inexpensive, frequent, access to space. Faced with this challenge during the International Space Station (ISS) build era, when other Space Shuttle manifesting opportunities are unavailable, a "proof of concept" cryostat has been developed to demonstrate the ability to accommodate low temperature science investigations within the constraints of the Hitchhiker siderail carrier. The Hitchhiker siderail carrier is available on a "mass available" basis during the ISS build era. In fact, several hitchhiker payloads flew with the deployment of the Unity module. Hitchhiker siderail carrier payloads have historically flown an average of about four times a year. A hybrid Solid Neon - Superfluid Helium cryostat has been developed with Janis Research Company to accommodate instruments of 16.5 cm diameter and 30 cm. length. This hybrid approach was taken in part to provide adequate on-orbit lifetime for instruments with high (conducted) heat loads from the instrumentation wiring. Mass, volume, lifetime and the launch hold scenario were all design drivers. In addition, with Ball Aerospace and Technologies Corporation, a multichannel VME architecture Germanium Resistance Thermometer (GRT) readout and heater control servo system has been developed. In a flight system, the cryostat and electronics payloads would be umbilically attached in a paired Hitchhiker siderail mount, and permit on-orbit command and telemetry capability. The results of performance tests of both the cryostat, and a helium sample instrument will be presented. The instrument features a self contained, miniaturized, nano-Kelvin resolution High Resolution Thermometer (HRT). This high level of thermal resolution is achieved through the utilization of a dc Superconducting Quantum Interference Device (SQUID). Although developed for the Low Temperature Microgravity Fundamental Physics investigator community, many design features are applicable in fields such as infrared and x-ray astronomy.

Nash, Alfred↗

Approximating the linear response of physical chaos

Abstract Parametric derivatives of statistics are highly desired quantities in prediction, design optimization and uncertainty quantification. In the presence of chaos, the rigorous computation of these quantities is certainly possible, but mathematically complicated and computationally expensive. Based on Ruelle’s formalism, this paper shows that the sophisticated linear response algorithm can be dramatically simplified in higher-dimensional systems featuring statistical homogeneity in the physical space. We argue that the contribution of the SRB (Sinai–Ruelle–Bowen) measure gradient, which is an integral yet the most cumbersome part of the full algorithm, is negligible if the objective function is appropriately aligned with unstable manifolds. This abstract condition could potentially be satisfied by a vast family of real-world chaotic systems, regardless of the physical meaning and mathematical form of the objective function and perturbed parameter. We demonstrate several numerical examples that support these conclusions and that present the use and performance of a simplified linear response algorithm. In the numerical experiments, we consider physical models described by differential equations, including Lorenz 96 and Kuramoto–Sivashinsky.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optical imaging spectroscopy

During the recent solar maximum the combination of imaging and spectroscopy in the visible part of the spectrum became a powerful tool for observational study of flares primarily because of the development of two-dimensional charge-coupled-device (CCD) arrays. In combination with appropriate new operational methods, this has led to the ability to observe, for the first time, the preflare and impulsive-phase physical processes associated with spatially resolved features of flare loops. As a result of concurrent theoretical developments, modeling progressed from an empirical to a physical level. This made it possible to interpret imaging spectra in terms of coronal pressure and heat flux, particle beam heating, chromospheric evaporation, and explosive chromospheric dynamics at the footpoints of flare loops. There is clear potential for further advances in the near future, taking advantage of improvements in digital recording speed (approx. 10-fold), number of photosensitive elements per array (approx. 10-fold), real-time data pre-reduction (potentially 10- to 100-fold), and using multiple CCD arrays. By the time of the next solar maximum imaging spectroscopy is expected to achieve spatial resolution or approx. arc 1 arc s, temporal resolution or approx. 5 s, and simultaneous critically-sampled spectroscopy of several lines and continua. As a result, continued increase in our understanding of the physical processes and configurations of solar flares in the chromosphere, temperature minimum region, and photosphere can be anticipated. Even greater progress toward a more global understanding of flares will obviously come about when simultaneous optical, X-ray, and gamma-ray imaging spectroscopy are possible.

Canfield, R. C.↗

Large and small scale circulation signatures of the ERS-1 SAR over the Gulf Stream

Since September 1991, the ERS-1 SAR (Synthetic Aperture Radar) has collected approximately 170 frames of ocean imagery on 28 passes over the western Gulf Stream in support of ESA experiment US8-2c. SAR signatures of the north wall are seen on nearly all passes, with modulation depth varying from 3% to 35% for 100 m samples. Many small and mesoscale circulation features associated with the Stream are evident. The detailed form of the signature varies considerably, however. Narrow bright or dark linear features appear to follow streamlines, and on one occasion a strong dark line was associated with an in situ measurement of a sharp current shear. Similarly, larger spatial scale changes in backscatter over the Stream were associated with in situ measurements of atmospheric stability transitions. Physical explanations for the narrow features are not so obvious. However, the accumulation of surfactants along converging current boundaries or local short wave straining and breaking appear plausible. These preliminary results strongly suggest that a wide swath (approximately 500 km) SAR with at least 100 m resolution would be a useful adjunct to existing satellite AVHRR (Advanced Very High Resolution Radiometer) imagery.

Beal, R.↗

Multidisciplinary Design Optimization of a Transonic Truss-Braced Wing using Physics-Based Models

Economic and environmental forces have placed pressure on the aviation industry to produce future aircraft designs with substantial improvements over those flying today. In order to meet these ambitious goals, new concepts such as the Transonic Truss-Braced Wing (TTBW) are being considered which diverge from the traditional tube-and-wing design. While this concept offers potential performance benefits over its traditional counterpart, it also features more coupling between various physics disciplines that must be considered during the design of the concept. This unique challenge provides a ripe opportunity for the application of multidisciplinary design optimization tool sets. The final work will couple together the mission analysis capability of Aviary with OpenAeroStruct for aerodynamic analysis and TACS for structural analysis. Using these tools we will preform a design optimization on the TTBW concept minimizing design fuel burn. The optimization will include design variables for mission trajectory, wing geometry, and structural sizing variables.

mbsae↗

Data-Driven Cyber-Attack Detection for PV Farms via Time-Frequency Domain Features

The internetworking of grid-connected power electronics converters (PECs) in photovoltaic (PV) farms has inevitably expanded the cyber-attack surfaces. Here this paper presents a comprehensive study on cyber-attack detection and diagnosis for PEC-enabled PV farms via single waveform sensor to distinguish between normal conditions, open-circuit faults, short-circuit faults, and cyber-attacks. To our knowledge, this has not been attempted before. Firstly, we propose frequency-domain magnitude-based residuals to identify short-circuit faults and a time-domain mean current vector-based feature to distinguish open-circuit faults from other threats. These features can fully reflect the specific physical characteristics of PV farms during threat duration. Secondly, unlike micro phasor measurement units (µPMU) and raw electric waveform-based methods, the proposed innovative features can address novel cyber-attacks that are excluded from the training process. Thirdly, an online hardware-in-the-loop (HIL) testbed using the OPAL-RT real-time digital simulator has verified the effectiveness. The monitoring system runs in real-time while using HIL as an operational solar farm and a National Instruments (NI) data acquisition card as the electric waveform sensor at the point of coupling.

42 ENGINEERING↗

Co-Occurring Atmospheric Features and Their Contributions to Precipitation Extremes

Object-based identification algorithms for atmospheric features are commonly utilized to attribute global precipitation. This study employs a systematic approach to examine feature co-occurrences and their relationships to mean and extreme precipitation. Four features are identified using existing data sets for atmospheric rivers (ARs), mesoscale convective systems (MCSs), low-pressure systems (LPSs), and fronts (FTs). Often, a single atmospheric phenomenon satisfies the criteria set by multiple feature identification algorithms, yielding an association between precipitation and multiple features. Over the extra-tropics, the number of features attributed to a single event typically increases with precipitation intensity. Over two-thirds of the precipitation is from co-occurring features, with a considerable fraction related to AR-FT co-occurrences. Over the tropics, about one-quarter of precipitation is associated with co-occurring features, with LPS-MCS co-occurrences contributing substantially in monsoon regions. MCSs are the leading single-feature contributors over tropical land and oceans. In the extra-tropics, FTs, ARs, and their co-occurrences account for over half of the total precipitation over oceans. AR-FT-MCS and FT-MCS co-occurrences contribute to extremes (precipitation exceeding the 95th percentile) over both oceans (over 30%) and land (over 20%). Any combination of features involving MCSs shows a larger contribution to high percentiles of precipitation intensity. A case analysis indicates that AR-FT-MCS co-occurrences exhibit convective instability and deep vertical motion, suggesting that the feature trackers and reanalysis are capturing physics relevant to both convective and frontal systems. The results here emphasize the need for simultaneous identifications of multiple features when attributing precipitation to atmospheric phenomena.

54 ENVIRONMENTAL SCIENCES↗

Use Attainability Analysis for Upper Sandia Canyon

This document presents a use attainability analysis (UAA) for the perennial segment of Upper Sandia Canyon, which is located within the Los Alamos National Laboratory (LANL) property near Los Alamos, New Mexico.1 This UAA is consistent with 20.6.4.15 New Mexico Administrative Code (NMAC) (New Mexico Environment Department [NMED] 2011c), which describes the perennial segment as “Sandia Canyon from Sigma Canyon upstream to LANL [National Pollutant Discharge Elimination System] NPDES outfall 001.” The perennial segment’s designated uses are coldwater aquatic life, livestock watering, wildlife habitat, and secondary contact. 40 Code of Federal Regulations (CFR) § 131.10(g) permits a state to remove a designated use that is not an existing use (as defined in 40 CFR §131.3), if a UAA demonstrates that naturally occurring pollutant concentrations prevent the attainment of the use or if physical conditions related to the natural features of the water body preclude the attainment of the aquatic life protection use. This UAA considers whether natural physical conditions in Upper Sandia Canyon, specifically air and/or water temperatures, prevent the designated aquatic life use water temperature limits (i.e., coldwater) from being attained in the perennial segment. The weight of evidence presented in this UAA supports the conclusion that, based on air-water temperature modeling and instream thermograph data, the coolwater aquatic life designated use is currently the attainable use. Accordingly, it is recommended that the coolwater aquatic life designated use replace the coldwater aquatic life designated use in the Upper Sandia Canyon assessment unit (AU).

54 ENVIRONMENTAL SCIENCES↗

Impedance Response Influenced by Variability in the Random Distribution of Physical Properties of Coated Materials in Two-Dimensional Space

Heterogeneous physical characteristics of a system featuring a single-layer film on a metallic surface have been explored via its impedance response. The Nyquist plot showed a distorted semicircle, indicative of the system's unique distribution characteristics. Utilizing a copula-based probability method, a two-dimensional deterministic impedance model was successfully integrated, accounting for spatial physical properties such as permittivity and electrical conductivity. This strategy enabled in-depth exploration and mechanistic quantification of a broad spectrum of properties. A quantitative understanding of impedance signal alterations, characterized by normally or log-normally correlated variables, was achieved through the variation in aspect ratio and characteristic frequency of the impedance spectra. Log-normally distributed electrical properties provided a superior representation of the distorted impedance spectra. As coefficient of variation (CV) values fluctuated, the aspect ratio and characteristic frequency showed heightened sensitivity to log-normal permittivity compared to log-normal electrical conductivity. Notably, a marked positive linear correlation between electrical properties resulted in an impedance response that approximated perfect semicircular spectra. The variability in the electrical properties' distribution was demonstrated by considering the correlation coefficient between electrical conductivity and the z-direction position. Furthermore, the highest aspect ratio of the impedance spectra was observed when the electrical conductivity was randomly distributed across the z-direction space.

36 MATERIALS SCIENCE↗

Parametric reduced-order modeling for component-oriented treatment and localized nonlinear feature inclusion

Abstract We propose coupling a physics-based reduction framework with a suited response decomposition technique to derive a component-oriented reduction (COR) approach, which is suitable for assembly systems featuring localized nonlinearities. Dependencies on influencing parameters are injected into the reduced-order model (ROM), thus ensuring robustness and validity over a domain of parametric inputs, while capturing nonlinear effects. The implemented approach employs individual component modes to capture localized features while additionally relying on reduced modes of a global nature to approximate the system’s dynamics accurately. The global modes are derived from a linear monolithic system, defined as a result of a coordinate separation scheme, which permits the proposed COR-ROM to naturally couple the response between linear and nonlinear subdomains. The derived low-order representation utilizes a proper orthogonal decomposition projection and is additionally reinforced with the inclusion of a hyper-reduction technique to capture the underlying high-fidelity model response while providing accelerated computations. The resulting approach is exemplified in the synthetic case studies of a four-story shear frame with multiple nonlinear regions driven by hysteresis and a large-scale kingpin connection featuring plasticity.

Vlachas, Konstantinos (ORCID:000000029124219X)↗

Studies of Westward Electrojets and Field-Aligned Currents in the Magnetotail During Substorms: Implications for Magnetic Field Models

This section outlines those tasks undertaken in the final year that contribute integrally to the overarching project goals. Fast, during the final year, it is important to note that the project benefited greatly with the addition of a Boston University graduate student, Ms. Karen Hirsch. Jointly, we made substantial progress on the development of and improvements to magnetotail magnetic field and plasma models. The ultimate aim of this specific task was to assess critically the utility of such models for mapping low-altitude phenomena into the magnetotail (and vice-versa). The bulk of this effort centered around the finite-width- magnetotail convection model developed by and described by Spence and Kivelson (J. Geophys. Res., 98, 15,487, 1993). This analytic, theoretical model specifies the bulk plasma characteristics of the magnetotail plasma sheet (number density, temperature, pressure) across the full width of the tail from the inner edge of the plasma sheet to lunar distances. Model outputs are specified by boundary conditions of the source particle populations as well as the magnetic and electric field configuration. During the reporting period, we modified this code such that it can be interfaced with the auroral particle precipitation model developed by Dr. Terry Onsager. Together, our models provide a simple analytic specification of the equatorial distribution of fields and plasma along with their low-altitude consequences. Specifically, we have built a simple, yet powerful tool which allows us to indirectly 'map' auroral precipitation signatures (VDIS, inverted-V's, etc.) measured by polar orbiting spacecraft in the ionosphere, to the magnetospheric equatorial plane. The combined models allow us to associate latitudinal gradients measured in the ion energy fluxes at low-altitudes with the large-scale pressure gradients in the equatorial plane. Given this global, quasi-static association, we can then make fairly strong statements regarding the location of discrete features in the context of the global picture. We reported on our initial study at national and international meetings and published the results of our predictions of the low-altitude signatures of the plasma sheet. In addition, the PI was invited to contribute a publication to the so-called 'Great Debate in Space Physics' series that is a feature of EOS. The topic was on the nature of magnetospheric substorms. Specific questions of the when and where a substorm occurs and the connection between the auroral and magnetospheric components were discussed in that paper. This paper therefore was derived exclusively from the research supported by this grant. Attachment: Empirical modeling of the quite time nightside magnetosphere.' 'CRRES observations of particle flux dropout event.' The what, where, when, and why of magnetospheric substorm triggers'. and 'Low altitude signature of the plasma sheet: model prediction of local time dependence'.

Spence, Harlan E.↗

Skeletides: A Modular, Simplified Physical Model of Protein Secondary Structure

Three-dimensional (3D) models are essential for visualization and conceptual understanding of complex architectures such as protein structure. Although there is a plethora of software platforms that allow digital depictions of protein structure at an atomic level in silico, physical models are needed to convey an intuitive understanding of biomolecular architecture. However, it is a challenge to represent all the relevant features of proteins in a single physical model due to their sheer structural complexity. Here, we describe a modular protein model that focuses only on representation of the secondary structure—the underlying structural skeleton. The simplified model consists of amino acid units, which can be linked together to reproduce the two most fundamental structural features of protein secondary structure: the relative positions of the amino acid alpha carbon atoms, and the intra-main chain hydrogen bonding pattern. We use 3D printing and magnets to create a set of three modular amino acid building blocks, which when linked together into a chain, can faithfully represent alpha helices, beta sheets, and turns. These simple to make models can be used to quickly assemble the alpha carbon trace of an entire protein domain, which conveys a tactile experience of the complexity of protein skeletal architecture. These models highlight the modularity of protein structure: where a single structural unit, the amino acid, can be linked together to form a larger, regular secondary structure. These models also have a propensity to spontaneously organize into alpha helices and beta sheets, as demonstrated by their ability to autonomously assemble when placed in a circulating water tank. These models provide a missing educational tool to expand knowledge of protein structure, foster deeper insight into protein folding, and inspire greater interest in biomacromolecular architecture.

36 MATERIALS SCIENCE↗

Ion partitioning in the hot Io torus - The influence of S2 outgassing

An alternative time-independent model of the ion partitioning in the hot Io torus is proposed which introduces the ratio of sulfur to oxygen in the neutral source as a free parameter. Measurements of the ion abundances in the torus plasma are presented and discussed, noting some ambiguities and identifying the features that are well established. Physical processes important to the understanding of the ion partitioning calculation are reviewed. The results of the model are discussed in the context of observational constraints, and spectroscopic constraints are discussed. It is concluded that a bimodal source model, together with a small percentage of hot electrons and a relatively short diffusion time scale, can account for the principal observational features without invoking significant time variability. In particular, the O III deficiency observed in 1981 can be obtained in a model that produces other aspects of the torus ion partitioning measured during the Voyager 1 encounter.

Moreno, M. A.↗

Herschel and the Molecular Universe

Over the next decade, space-based missions will open up the universe to high spatial and spectral resolution studies at infrared and submillimeter wavelengths. This will allow us to study, in much greater detail, the composition and the origin and evolution of molecules in space. Moreover, molecular transitions in these spectral ranges provide a sensitive probe of the dynamics and the physical and chemical conditions in a wide range of objects at scales ranging from budding planetary systems to galactic and extragalactic sizes. Hence, these missions provide us with the tools to study key astrophysical and astrochemical processes involved in the formation and evolution of planets, stars, and galaxies. These new missions can be expected to lead to the detection of many thousands of new spectral features. Identification, analysis and interpretation of these features in terms of the physical and chemical characteristics of the astronomical sources will require detailed astronomical modeling tools supported by laboratory measurements and theoretical studies of chemical reactions and collisional excitation rates on species of astrophysical relevance. These data will have to be made easily accessible to the scientific community through web-based data archives. In this paper, we will review the Herschel mission and its expected impact on our understanding of the molecular universe.

Tielens, A. G. G. M.↗

Understanding structure-processing relationships in metal additive manufacturing via featurization of microstructural images

Understanding and predicting accurate property-structure-processing relationships for additively manufactured components is important for both forward and inverse design of robust, reliable parts and assemblies. While direct mapping of process parameters to properties is sometimes plausible, it is often rendered difficult due to poor microstructural control. Exploring the direct relationship between processing conditions and microstructural features can thus provide significant physical insights and aid the overall design process. Here, in this study, we develop an automated high-throughput framework to simulate an uncertainty-aware additive manufacturing (AM) process, characterize microstructural images, and extract meaningful features/descriptors. A kinetic Monte Carlo (KMC) based model of the AM process is used to simulate microstructural evolution for a diverse set of experimentally relevant processing conditions. We perform a parametric study to explore the relationship between microstructural features and processing conditions. Our results indicate that a many-to-one mapping can exist between processing conditions and typical descriptors; therefore, multiple descriptors are thus necessary to unambiguously represent microstructural images. Our work provides crucial quantitative and qualitative in-formation that would aid in the selection of features for microstructural images. Featurized microstructures could then be utilized to build data-driven models for predictive control of microstructures and thereby properties of additively manufactured components.

36 MATERIALS SCIENCE↗

Anomaly Identification of Synchronized Voltage Waveform for Situational Awareness of Low Inertia Systems

Inverter-based resources (IBRs) such as photovoltaics (PVs), wind turbines, and battery energy storage systems (BESSs) are widely deployed in low-carbon power systems. However, these resources typically do not provide the inertia needed for grid stability, resulting in a low-inertia power system. IBRs and lack of inertia have been known to cause anomalies such as waveform distortions and wideband oscillations in power systems due to the limited inertia level, leading to increased generation trips and load shedding. Here, to achieve effective anomaly identification, this paper proposes a synchro-waveform-based algorithm utilizing real-time synchronized voltage waveform measurements from waveform measurement units (WMUs). In the proposed method, different physical characteristics, as well as statistical features, are extracted from synchronized voltage waveform measurements to filter anomalies. Then, the anomaly identification approach based on the random forest is developed and deployed into the FNET/GridEye system considering trade-offs among accuracy, computational burden, and deployment cost. Moreover, four WMUs are specially designed and deployed on Kauai Island to receive instantaneous synchronized voltage waveform measurements. To verify the performance of the proposed algorithm, different experiments are carried out with collected field test data. The result demonstrates that the performance of the proposed synchro-waveform-based anomaly categorization algorithm can accurately identify anomalies 95.35% of the time, which has comparable performance among benchmarking algorithms.

Situational awareness↗