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At least 1,675 records · Page 93

Composite box beam analysis - Theory and experiments

Beam theory is widely used as a first approximation in numerous structural applications. When applied to composite beams, the accuracy of beam theory becomes questionable because (1) the shearing and warping deformations become significant, as the shearing stiffness of composite laminates is often very low, and (2) several elastic couplings can occur that strongly influence the behavior of composite beams. The torsional behavior of thin-walled composite beams has important implications for aeronautical structures and is deeply modified by the above nonclassical effects. This paper presents two comprehensive analysis methodologies for composite beams and describes experimental results obtained from a thin-walled, rectangular cross-sectional beam. The theoretical predictions are found in good agreement with the observed twist and strain distributions. Out-of-plane torsional warping of the cross-section is found to be the key factor for an accurate modeling of the torsional behavior of such structures.

Bauchau, O. A.↗

The virial theorem for the polarizable continuum model

The electronic virial theorem is extended to molecular systems within the framework of the Polarizable Continuum Model (PCM) to describe solvation effects. The theorem is given in the form of a relation involving the components of the energy (kinetic and potential) of a molecular solute and its electrostatic properties (potential and field) at the boundary of the cavity in the continuum medium. The virial theorem is also derived in the presence of the Pauli repulsion component of the solute-solvent interaction. Furthermore, it is shown that these forms of the PCM virial theorem may be related to the virial theorem of more simple systems as a molecule in the presence of fixed point charges, and as an atom in a spherical box with confining potential.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modal Q Factor and Modal Overlap of Electrically Small Avionics Box

Estimating the electromagnetic field strength in avionics boxes and other small enclosures at the design stage requires an estimate of the Q factor of the cavity modes. When the enclosure is small, it is typically under-moded so that Q measurement techniques which are standard practice in over-moded reverberation chambers may not be a robust measure. Furthermore, practical antenna used to measure Q in a small cavity may have a strong influence on the result obtained, as reported by Tait et al, IEEE Trans. EMC 55 2 2012. This paper reports the results of testing to determine the Q factor of a small aperture enclosure, used in a statistical power balance model to predict the electric field strength. The contributors to the total Q are identified. A novel S(sub 11) curve fitting method to measure modal Q is introduced and compared with the time domain method for measuring Q.

Statistical Electromagnetics↗

Results and Lessons Learned From the DOE Commercial Building Partnerships: Preprint

Over the course of 5 years, NREL worked with commercial building owners and their design teams in the DOE Commercial Building Partnerships (CBP) to cut energy consumption by 50% in new construction (versus code) and by 30% in existing building pilot projects (versus code or pre-retrofit operational energy use depending on the preference of the Partner) using strategies that could be replicated across their building portfolios. A number of different building types were addressed, including supermarket, retail merchandise, combination big box (general merchandise and food sales), high rise office space, and warehouse. The projects began in pre-design and included a year of measurement data to evaluate performance against design expectations. Focused attention was required throughout the entire process to achieve a design with the potential to hit the energy performance target and to operate the resulting building to reach this potential. This paper will report quantitative results and cover both the technical and the human sides of CBP, including the elements that were required to succeed and where stumbling blocks were encountered. It will also address the impact of energy performance goals and intensive energy modeling on the design process innovations and best practices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

TPSAS-NF1676L-19238-DND

The 24-hour cycle of solar insolation drives diurnal cycles in Earth system processes critical to climate: radiation, convection, turbulence, and cloud processes. Cloud properties, temperature, radiative fluxes, and precipitation exhibit robust diurnal cycles as a result. The presence of these robust diurnal cycles fundamentally changes the time mean and variability of the TOA energy budget. Therefore, there is a need to understand the diurnal cycle contributions to the TOA energy budget in both observations and climate models. The first objective of this study is to quantify the diurnal cycle impact on the time mean and variability of the TOA energy budget in observations defined as the difference between TOA fluxes computed with diurnally uniform and diurnally varying cloud properties. The required observational input is observed from the combined Terra+Aqua Cloud and Earth's Radiant Energy System (CERES) data products ranging from June 2002 through October 2012. The second objective of this study is to evaluate the impact of known errors in the model diurnal cycle simulation on the time mean and variability of the TOA energy budget. The results indicate that (1) the diurnal cycle impacts on the regional time mean Tropical longwave and shortwave fluxes range from 1-3 W m 2 and 5 25 W m 2, respectively; (2) the diurnal cycle contributions to TOA flux variability exceeds 50% in land convective regions (e.g., central South America and central Africa);(3) the diurnal cycle contributions to the TOA shortwave and longwave flux time mean and variability in the CanAM4 GCM are too small in land convective regions due to errors in the diurnal distribution of convective clouds grid box errors exceed 100%.

Patrick C Taylor↗

Bio-inspired strategies for next-generation perovskite solar mobile power sources

Smart electronic devices are becoming ubiquitous due to many appealing attributes including portability, long operational time, rechargeability and compatibility with the user-desired form factor. Integration of mobile power sources (MPS) based on photovoltaic technologies with smart electronics will continue to drive improved sustainability and independence. With high efficiency, low cost, flexibility and lightweight features, halide perovskite photovoltaics have become promising candidates for MPS. Realization of these photovoltaic MPS (PV-MPS) with unconventionally extraordinary attributes requires new ‘out-of-box’ designs. Natural materials have provided promising designing solutions to engineer properties under a broad range of boundary conditions, ranging from molecules, proteins, cells, tissues, apparatus to systems in animals, plants, and humans optimized through billions of years of evolution. Applying bio-inspired strategies in PV-MPS could be biomolecular modification on crystallization at the atomic/meso-scale, bio-structural duplication at the device/system level and bio-mimicking at the functional level to render efficient charge delivery, energy transport/utilization, as well as stronger resistance against environmental stimuli (e.g., self-healing and self-cleaning). In this paper, we discuss the bio-inspired/-mimetic structures, experimental models, and working principles, with the goal of revealing physics and bio-microstructures relevant for PV-MPS. Here the emphasis is on identifying the strategies and material designs towards improvement of the performance of emerging halide perovskite PVs and strategizing their bridge to future MPS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hypothesis testing via AI: Generating physically interpretable models of scientific data with machine learning (Full Technical Report)

Deep learning has demonstrated an exceptional ability to solve complex tasks (an engineering success); however, it has done so at the expense of the ability to generate new knowledge (a scientific failure). We propose an alternative framework—entitled Deep Symbolic Regression (DSR)—in which artificial neural networks (NNs) rapidly generate hypotheses about physical relationships among inputs. This framework bypasses the need to interpret an NN altogether, while still leveraging the representational power of deep learning. The resulting models are tractable mathematical expressions, which are inherently and readily human interpretable and can provide insights into underlying physical phenomena. Further, we fold this methodology into the scientific process by allowing the scientist to directly integrate a priori knowledge and beliefs to accelerate learning. We demonstrate this methodology on symbolic regression—the problem of rediscovering underlying expressions describing a dataset—and achieve state-of-the-art performance across a wide variety of symbolic regression problems. Further, we generalize our DSR framework to apply to the more general class of symbolic optimization problems, in which one seeks to optimize a sequence of symbols or “tokens” under a black-box reward function. Examples of other symbolic optimization problems include neural architecture search and computational antibody design. Our generalized tool, Deep Symbolic Optimization (DSO), has been demonstrated on the task of learning symbolic control policies for reinforcement learning environments, and has been adopted as an enabling capability for computational antibody design.

97 MATHEMATICS AND COMPUTING↗

A general model for retroviral capsid pattern recognition by TRIM5 proteins

Restriction factors are intrinsic cellular defense proteins that have evolved to block microbial infections. Retroviruses such as HIV-1 are restricted by TRIM5 proteins, which recognize the viral capsid shell that surrounds, organizes, and protects the viral genome. TRIM5α uses a SPRY domain to bind capsids with low intrinsic affinity ( K D >1 mM), and therefore requires higher-order assembly into a hexagonal lattice to generate sufficient avidity for productive capsid recognition. TRIMCyp, on the other hand, binds HIV-1 capsids through a cyclophilin A domain, which has a well-defined binding site and higher ( K D ~10 μM) affinity for isolated capsid subunits. It has therefore been argued that TRIMCyp proteins may have dispensed with the need for higher-order assembly to function as antiviral factors. Here, we show that, consistent with its high degree of sequence similarity with TRIM5α, the TRIMCyp B-box 2 domain shares the same ability to self-associate and facilitate assembly of a TRIMCyp hexagonal lattice that can wrap about the HIV-1 capsid. We also show that under stringent experimental conditions, TRIMCyp-mediated restriction of HIV-1 is indeed dependent on higher-order assembly. Both forms of TRIM5 therefore use the same mechanism of avidity-driven capsid pattern recognition. IMPORTANCE Rhesus macaques and owl monkeys are highly resistant to HIV-1 infection due to the activity of TRIM5 restriction factors. The rhesus macaque TRIM5α protein blocks HIV-1 through a mechanism that requires self-assembly of a hexagonal TRIM5α lattice around the invading viral core. Lattice assembly amplifies very weak interactions between the TRIM5α SPRY domain and the HIV-1 capsid. Assembly also promotes dimerization of the TRIM5α RING E3 ligase domain, resulting in synthesis of polyubiquitin chains that mediate downstream steps of restriction. In contrast to rhesus TRIM5α, the owl monkey TRIM5 homolog, TRIMCyp, binds isolated HIV-1 CA subunits more tightly through its cyclophilin A domain, and was therefore thought to act independent of higher-order assembly. Here, we show that TRIMCyp shares the assembly properties of TRIM5α and that both forms of TRIM5 use the same mechanism of hexagonal lattice formation to promote viral recognition and restriction.

Wagner, Jonathan M.↗

Robustness of Deep Learning Classification to Adversarial Input on GPUs: Asynchronous Parallel Accumulation Is a Source of Vulnerability

The ability of machine learning (ML) classification models to resist small, targeted input perturbations—known as adversarial attacks—is a key measure of their safety and reliability. We show that floating-point non associativity (FPNA) coupled with asynchronous parallel programming on GPUs is sufficient to result in misclassification, without any perturbation to the input. Additionally, we show that this misclassification is particularly significant for inputs close to the decision boundary and that standard adversarial robustness results may be overestimated up to 4.6 when not considering machine-level details. We first study a linear classifier, before focusing on standard Graph Neural Network (GNN) architectures and datasets used in robustness assessments. We develop a novel black-box attack using Bayesian optimization to discover external workloads that can change the instruction scheduling which bias the output of reductions on GPUs and reliably lead to misclassification. Motivated by these results, we present a new learnable permutation (LP) gradient-based approach to learning floating-point operation orderings that lead to misclassifications. The LP approach provides a worst-case estimate in a computationally efficient manner, avoiding the need to run identical experiments tens of thousands of times over a potentially large set of possible GPU states or architectures. Finally, using instrumentation-based testing, we investigate parallel reduction ordering across different GPU architectures under external background workloads, when utilizing multi-GPU virtualization, and when applying power capping. Our results demonstrate that parallel reduction ordering varies significantly across architectures under the first two conditions, substantially increasing the search space required to fully test the effects of this parallel scheduler-based vulnerability. These results and the methods developed here can help to include machine-level considerations into adversarial robustness assessments, which can make a difference in safety and mission critical applications.

Shanmugavelu, Sanjif [Maxeler Technologies, a Groq↗

Ergodic and nonergodic many-body dynamics in strongly nonlinear lattices

The study of nonlinear oscillator chains in classical many-body dynamics has a storied history going back to the seminal work of Fermi et al. [Los Alamos Scientific Laboratory Report No. LA-1940, 1955 (unpublished)]. Here, we introduce a family of such systems which consist of chains of N harmonically coupled particles with the nonlinearity introduced by confining the motion of each individual particle to a box or stadium with hard walls. The stadia are arranged on a one-dimensional lattice but they individually do not have to be one dimensional, thus permitting the introduction of chaos already at the lattice scale. For the most part we study the case where the motion is entirely one dimensional. We find that the system exhibits a mixed phase space for any finite value of N . Computations of Lyapunov spectra at randomly picked phase space locations and a direct comparison between Hamiltonian evolution and phase space averages indicate that the regular regions of phase space are not significant at large system sizes. While the continuum limit of our model is itself a singular limit of the integrable sinh Gordon theory, we do not see any evidence for the kind of nonergodicity famously seen in the work of Fermi et al. Finally, we examine the chain with particles confined to two-dimensional stadia where the individual stadium is already chaotic and find a much more chaotic phase space at small system sizes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Robust and Flexible Design for GCEP Unattended Online Enrichment Monitoring: An OLEM Collection Node Network

Oak Ridge National Laoratory (ORNL) has engineered an on-line enrichment monitor (OLEM) to continuously measure U-235 emissions from the UF6 gas flowing through a unit header pipe of a gas centrifuge enrichment plant (GCEP) as a component of the International Atomic Energy Agency s (IAEA) new generation of technology to support enrichment plant safeguards1. In contrast to other enrichment monitoring approaches, OLEM calibrates and corrects for the pressure and temperature dependent UF6 gas-density without external radiation sources by using the inherent unit header pipe pressure dynamics and combining U-235 gamma-ray spectrometery using a shielded NaI detector with gas pressure and temperature data near the spectrum measurement point to obtain the enrichment of the gas as a function of time. From a safeguards perspective, OLEM can provide early detection of a GCEP being misused for production of highly enriched uranium, but would not detect directly the isolation and use of a cascade within the production unit to produce HEU. OLEM may also reduce the number of samples collected for destructive assay and, if coupled with load cell monitoring, could support isotope mass balance verification and unattended cylinder verification. The earlier paper presented OLEM as one component along with shared load cells and unattended cylinder verification, in the IAEA emering toolbox for unattended instruments at GCEPs1 and described the OLEM concept and how previous modeling studies and field measurements helped confirm the viability of a passive on-line enrichment monitor for meeting IAEA objectives and to support the development of performance targets. Phase I of the United States Support Program (USSP) OLEM project completed a preliminary hardware, software and communications design; phase II will build and test field prototypes in controlled laboratory settings and then at an operational facility. That paper also discussed many of the OLEM collection node commercial off the shelf (COTS) components and summarized the OLEM collection node data security provisions. This paper will discuss a secure and redundant network of OLEM collection nodes, auxiliary detection units and supporting junction boxes distributed throughout a facility for monitoring enrichment on product, feed and tails unit header pipes; the purpose and capability of the built-in Electronic Optical Sealing System (EOSS) network gateway; and a network approach for obtaining reliable and authenticated pressure measurements.

Younkin, James R↗

Detection efficiency measurement and operational tests of the X-Arapuca for the first module of DUNE far detector

The Deep Underground Neutrino Experiment (DUNE) is a dual-site experiment for long-baseline neutrino oscillation studies, able to resolve the neutrino mass hierarchy and measure δ$_{CP}$. DUNE will also have sensitivity to supernova neutrinos and to processes beyond the Standard Model, such as nucleon decay searches. The Far Detector (FD) will consist of four liquid argon TPC (17.5 kt total mass) with systems for the detection of charge and scintillation light produced by an ionization event. The charge detection system permits both calorimetry and position determination. In addition, the photon-detection system (PDS) enhances the detector capabilities for all DUNE physics drivers. The PDS of the first FD module consists of light collector modules placed in the inactive space between the innermost wire planes of the TPC anode. The light collectors, the so-called X-ARAPUCAS, are functionally a light trap that captures wavelength-shifted photons inside boxes with highly reflective internal surfaces where they are guided to Silicon Photo-multipliers (SiPM) by wavelength-shifting (WLS) bars. Functionality and operational tests of the X-ARAPUCAS to be installed in ProtoDUNE-SP phase II (FD DUNE prototype at the scale 1:20), as well as the measurement of their absolute detection efficiency is reported in this publication.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Designing a Framework for Solving Multiobjective Simulation Optimization Problems

Multiobjective simulation optimization (MOSO) problems are optimization problems with multiple conflicting objectives, where evaluation of at least one of the objectives depends on a black-box numerical code or real-world experiment, which we refer to as a simulation. Whereas an extensive body of research is dedicated to developing new algorithms and methods for solving these and related problems, it is challenging and time-consuming to integrate these techniques into real-world production-ready solvers. This is partly because of the diversity and complexity of modern state-of-the-art MOSO algorithms and methods and partly because of the complexity and specificity of many real-world problems and their corresponding computing environments. The complexity of this problem is only compounded when introducing potentially complex and/or domain-specific surrogate-modeling techniques, problem formulations, design spaces, and data acquisition functions. Here, this paper carefully surveys the current state of the art in MOSO algorithms, techniques, and solvers, as well as problem types and computational environments where MOSO is commonly applied. We then present several key challenges in the design of a parallel multiobjective simulation optimization framework (ParMOO) and how they have been addressed. Finally, we provide two case studies demonstrating how customized ParMOO solvers can be quickly built and deployed to solve real-world MOSO problems.

engineering design optimization↗

ZEB1 induces non-small cell lung cancer development by targeting microRNA-320a to increase the expression of RAD51AP1

Lung cancer is the most prevalent cancer worldwide, with its mortality rate reported to be in millions annually; one of the two subtypes is non-small cell lung cancer (NSCLC). In this study, we investigated the interactions and expressions of zinc finger E-box binding homeobox 1 (ZEB1), microRNA-320a (miR-320a) and RAD51-associated protein 1 (RAD51AP1) in NSCLC tissues to determine the roles of ZEB1 in regulation of miR-320a and RAD51AP1 in the development and metastasis of NSCLC. First, the expression levels of miR-320a and ZEB1 were quantified in NSCLC tissues and cells. Transfection assay was conducted to identify the effects of miR-320a on the progression of NSCLC cells. The interaction of miR-320a with ZEB1 and RAD51AP1 was predicted and verified using dual-luciferase reporter gene assay and chromatin immunoprecipitation assay. Finally, subcutaneous xenograft tumors of 6-week mice and metastatic model tumors of 8-week mice were established to further explore the in vivo effect of miR-320a/ZEB1/RAD51AP1 on NSCLC. The findings revealed a lower expression of miR-320a in NSCLC tissues and cells, while this result was reversed regarding ZEB1 expression. ZEB1 suppressed miR-320a expression and upregulation of miR-320a resulted in the reduction of proliferation, invasion and metastasis rate of NSCLC cells, and promoted NSCLC cell apoptosis. ZEB1 promoted the expression of RAD51AP1 via inhibition of miR-320a, promoting tumor growth in vivo. ZEB1 transcriptionally inhibited the expression of miR-320a and upregulated the expression of RAD51AP1, thereby promoting metastasis in NSCLC.

60 APPLIED LIFE SCIENCES↗

Structural Sizing of a Tow-Steered Truss-Braced Wing Box Test Article

Tailoring of composite laminates is traditionally performed by changing the orientation of straight fibers in one or more plies. Modern automated fiber placement machines facilitate placement of bundles of curved fibers (tows) in a process called tow-steering, but additional variables must be used to define the shapes of tow-steered fiber paths. In this paper, the design of a tow-steered truss-braced wing test article called the Structural Wing Experiment Evaluating Truss-bracing 15-ft concept (SWEET-15) is discussed. The SWEET-15 test article is scaled to 18.6% of the span length and chord width of a full-scale vehicle. The test article is designed to withstand +2.5-g (positive limit) and -1.0-g (negative limit) maneuvering loads with a factor of safety of 1.5 under strength and buckling constraints. Design studies were performed using commercial finite element analysis and optimization software in conjunction with a tow-steering modeling tool called ATSCOOL (Automated Tool for Steered COmposite Optimizable Laminates) developed at NASA Langley Research center. A 6.4% weight reduction in the upper cover panels was achieved using a tow-steered layup configuration.

Structural Optimization↗

Structural Sizing of a Tow-Steered Truss-Braced Wing Box Test Article

Tailoring of composite laminates is traditionally performed by changing the orientation of straight fibers in one or more plies. Modern automated fiber placement machines facilitate placement of bundles of curved fibers (tows) in a process called tow-steering, but additional variables must be used to define the shapes of tow-steered fiber paths. In this paper, the design of a tow-steered truss-braced wing test article called the Structural Wing Experiment Evaluating Truss-bracing 15-ft concept (SWEET-15) is discussed. The SWEET-15 test article is scaled to 18.6% of the span length and chord width of a full-scale vehicle. The test article is designed to withstand +2.5-g (positive limit) and -1.0-g (negative limit) maneuvering loads with a factor of safety of 1.5 under strength and buckling constraints. Design studies were performed using commercial finite element analysis and optimization software in conjunction with a tow-steering modeling tool called ATSCOOL (Automated Tool for Steered COmposite Optimizable Laminates) developed at NASA Langley Research center. A 6.4% weight reduction in the upper cover panels was achieved using a tow-steered layup configuration.

Composites↗

Preparing for safe and compliant open air demolition at Hanford's plutonium finishing plant - 15100

The Plutonium Finishing Plant (PFP), located in the 200 West Area of the U.S. Department of Energy (DOE) Hanford Site, began operations in 1949 and produced plutonium metal during the Cold War. Production was stopped in 1989, the facility was formally shut-down in 1996, and material stabilization completed in 2004. DOE contractor CH2M HILL Plateau Remediation Company (CH2M HILL) is tasked with the plant's deactivation, decommissioning, decontamination and demolition, to be completed by September 30, 2016. The project team, partnering with DOE-Richland Operations Office (DOE-RL), is exploring, evaluating and implementing efficiencies to safely and compliantly prepare the facility for demolition. Since 2008, employees have prepared approximately 75 percent of the complex for demolition. More than 90 percent of the 232 glove boxes have been removed from ventilation and more than 80 percent of pencil tank units have been dispositioned. As decontamination, deactivation and removal nears completion on the remaining glove boxes, pencil tanks and other radiological and chemical processing infrastructure, CH2M HILL and DOE-RL are making preparations to demolish PFP itself, a Hazardous Category II nuclear facility (HazCat II). Conventional techniques used to demolish buildings heavily contaminated with radiological hazards typically involve extensive hands-on work to remove Material at Risk (MAR) and decontaminate the building to low levels before conventional demolition techniques can be used to remove the building. A safe and more cost effective approach is packaging MAR located in hard to access areas of the plant and removing it during demolition. That process, combined with affixing remaining contamination to walls, floors and equipment, performing detailed air dispersion modeling before demolition and air monitoring and dust suppression during demolition, will reduce employee risk and is more efficient in demolishing a HazCat II facility. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

LOCAL SIMULATIONS OF THE MAGNETOROTATIONAL INSTABILITY IN CORE-COLLAPSE SUPERNOVAE

Bearing in mind the application of core-collapse supernovae, we study the nonlinear properties of the magnetorotational instability (MRI) by means of three-dimensional simulations in the framework of a local shearing box approximation. By systematically changing the shear rates that symbolize the degree of differential rotation in nascent proto-neutron stars (PNSs), we derive a scaling relation between the turbulent stress sustained by the MRI and the shear-vorticity ratio. Our parametric survey shows a power-law scaling between the turbulent stress (((w {sub tot}))) and the shear-vorticity ratio (g{sub q} ) as ((w {sub tot})){proportional_to}g {sup {delta}} {sub q} with an index of {delta} {approx} 0.5. The MRI-amplified magnetic energy has a similar scaling relative to the turbulent stress, while the Maxwell stress has a slightly smaller power-law index ({approx}0.36). By modeling the effect of viscous heating rates from MRI turbulence, we show that the stronger magnetic fields, or the larger shear rates initially imposed, lead to higher dissipation rates. For a rapidly rotating PNS with a spin period in milliseconds and with strong magnetic fields of 10{sup 15} G, the energy dissipation rate is estimated to exceed 10{sup 51} erg s{sup -1}. Our results suggest that the conventional magnetohydrodynamic (MHD) mechanism of core-collapse supernovae is likely to be affected by MRI-driven turbulence, which we speculate, on the one hand, could harm the MHD-driven explosions due to the dissipation of the shear rotational energy at the PNS surface; or, on the other hand, its energy deposition might be potentially favorable for the working of the neutrino-heating mechanism.

79 ASTRONOMY AND ASTROPHYSICS↗