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At least 1,801 records · Page 100

Reaction losses of charged particles in CsI(Tl) crystals

To efficiently detect energetic light charged particles, it is common to use arrays of energy-loss telescopes involving two or more layers of detection media. As the energy of the particles increases, thicker layers are usually needed. However, carrying out measurements with thick-telescopes may require corrections for the losses due to nuclear reactions induced by the incident particles on nuclei within the detector and for the scattering of incident particles out of the detector, without depositing their full energy in the active material. In this paper, we develop a method for measuring such corrections and determine the reaction and out-scattering losses for data measured with the silicon-CsI(Tl) telescopes of the newly developed HiRA10 array. Here, the extracted efficiencies are in good agreement with model predictions using the GEANT4 reaction loss algorithm for Z = 1 and Z = 2 isotopes. After correcting for the HiRA10 geometry, we obtain a general function that describes the loss of efficiency due to reaction losses in CsI(Tl) crystals as a function of range.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An end-to-end deep learning solution for automated LiDAR tree detection in the urban environment

Cataloging and classifying trees in the urban environment is a crucial step in urban and environmental planning; however, manual collection and maintenance of this data is expensive and time-consuming. Although algorithmic approaches that rely on remote sensing data have been developed for tree detection in forests, they generally struggle in the more varied urban environment. This work proposes a novel end-to-end deep learning method for the detection of trees in the urban environment from remote sensing data. Specifically, we develop and train a novel PointNet-based neural network architecture to predict tree locations directly from LiDAR data augmented with multi-spectral imagery. We compare this model to a number of high-performing baselines on a large and varied dataset in the Southern California region, and find that our method outperforms all baselines in terms of tree detection ability (75.5% F-score) and positional accuracy (2.28 meter root mean squared error), while being highly efficient. We then analyze and compare the sources of errors, and how these reveal the strengths and weaknesses of each approach. Our results highlight the importance of fusing spectral and structural information for remote sensing tasks in complex urban environments.

54 ENVIRONMENTAL SCIENCES↗

Deep medical image analysis with representation learning and neuromorphic computing

Deep learning is increasingly used in medical imaging, improving many steps of the processing chain, from acquisition to segmentation and anomaly detection to outcome prediction. Yet significant challenges remain: (i) image-based diagnosis depends on the spatial relationships between local patterns, something convolution and pooling often do not capture adequately; (ii) data augmentation, the de facto method for learning three-dimensional pose invariance, requires exponentially many points to achieve robust improvement; (iii) labelled medical images are much less abundant than unlabelled ones, especially for heterogeneous pathological cases; and (iv) scanning technologies such as magnetic resonance imaging can be slow and costly, generally without online learning abilities to focus on regions of clinical interest. To address these challenges, novel algorithmic and hardware approaches are needed for deep learning to reach its full potential in medical imaging.

60 APPLIED LIFE SCIENCES↗

Materials challenges and opportunities for quantum computing hardware

Combatting noise on the platform The potential of quantum computers to solve problems that are intractable for classical computers has driven advances in hardware fabrication. In practice, the main challenge in realizing quantum computers is that general, many-particle quantum states are highly sensitive to noise, which inevitably causes errors in quantum algorithms. Some noise sources are inherent to the current materials platforms. de Leon et al. review some of the materials challenges for five platforms for quantum computers and propose directions for their solution. Science , this issue p. eabb2823

Science & Technology - Other Topics↗

Virtual Time III, Part 1: Unified Virtual Time Synchronization for Parallel Discrete Event Simulation

Algorithms for synchronization of parallel discrete event simulation have historically been divided between conservative methods that require lookahead but not rollback, and optimistic methods that require rollback but not lookahead. In this paper we present a new approach in the form of a framework called Unified Virtual Time (UVT) that unifies the two approaches, combining the advantages of both within a single synchronization theory. Whenever timely lookahead information is available, a logical process (LP) executes conservatively using an irreversible event handler. When lookahead information is not available the LP does not block, as it would in a classical conservative execution, but instead executes optimistically using a reversible event handler. The switch from conservative to optimistic synchronization and back is decided on an event-by-event basis by the simulator, transparently to the model code. UVT treats conservative synchronization algorithms as optional accelerators for an underlying optimistic synchronization algorithm, enabling the speed of conservative execution whenever it is applicable, but otherwise falling back on the generality of optimistic execution. We describe UVT in a novel way, based on fundamental invariants, monotonicity requirements, and synchronization rules. UVT permits zero-delay messages and pays careful attention to tie-handling using superposition. We prove that under fairly general conditions a UVT simulation always makes progress in virtual time. This is Part 1 of a trio of papers describing the UVT framework for PDES, mixing conservative and optimistic synchronization and integrating throttling control.

97 MATHEMATICS AND COMPUTING↗

Hyper-Differential Sensitivity Analysis of Uncertain Parameters in PDE-Constrained Optimization

Many problems in engineering and sciences require the solution of large scale optimization constrained by partial differential equations (PDEs). Though PDE-constrained optimization is itself challenging, most applications pose additional complexity, namely, uncertain parameters in the PDEs. Uncertainty quantification (UQ) is necessary to characterize, prioritize, and study the influence of these uncertain parameters. Sensitivity analysis, a classical tool in UQ, is frequently used to study the sensitivity of a model to uncertain parameters. In this article, we introduce "hyper-differential sensitivity analysis" which considers the sensitivity of the solution of a PDE-constrained optimization problem to uncertain parameters. Our approach is a goal-oriented analysis which may be viewed as a tool to complement other UQ methods in the service of decision making and robust design. We formally define hyper-differential sensitivity indices and highlight their relationship to the existing optimization and sensitivity analysis literatures. Assuming the presence of low rank structure in the parameter space, computational efficiency is achieved by leveraging a generalized singular value decomposition in conjunction with a randomized solver which converts the computational bottleneck of the algorithm into an embarrassingly parallel loop. Two multi-physics examples, consisting of nonlinear steady state control and transient linear inversion, demonstrate efficient identification of the uncertain parameters which have the greatest influence on the optimal solution.

97 MATHEMATICS AND COMPUTING↗

Multivariate interactive digital analysis system /MIDAS/ - A new fast multispectral recognition system

The MIDAS system is a prototype, multiple-pipeline digital processor mechanizing the multivariate-Gaussian, maximum-likelihood decision algorithm operating at 200,000 pixels/second. It incorporates displays and film printer equipment under control of a general purpose midi-computer and possesses sufficient flexibility that operational versions of the equipment may be subsequently specified as subsets of the system.

Kriegler, F.↗

A geostationary longitude acquisition planning algorithm

The paper is concerned with the phase of the geosynchronous mission termed station acquisition, which involves the maneuvering of a spacecraft to its geostationary longitude by means of the spacecraft propulsion system. An algorithm which assists in maneuver planning is described, and examples of its use are presented. The algorithm can be applied when sequences of more than three maneuvers are to be expected. While, in general, three maneuvers are sufficient to achieve the desired end conditions when orbital mechanics are the only consideration, operational considerations may add constraints resulting in an increased number of maneuvers required.

Petruzzo, C. J.↗

Analysis techniques for multivariate root loci

Analysis and techniques are developed for the multivariable root locus and the multivariable optimal root locus. The generalized eigenvalue problem is used to compute angles and sensitivities for both types of loci, and an algorithm is presented that determines the asymptotic properties of the optimal root locus.

Thompson, P. M.↗

Contrast reduction by the atmosphere and retrieval of nonuniform surface reflectance

A radiative transfer model is developed which gives the upward radiance at nadir for any 1-D Lambertian surface reflectance. This model is used to depict the atmospheric effect on the transmittance of contrast for any 1-D surface reflectance. Here by contrast we mean a general variation of the radiation field across the image. With the aid of this model an inversion algorithm is developed for retrieval of true surface reflectance from high resolution satellite data (e.g., Landsat). This inversion technique can be a useful tool for extraction of surface reflectance from satellite data in the case of a surface reflectance variable in one dimension only (e.g., seashore or near borders of big fields). A sensitivity study of the inversion procedure on the knowledge of atmospheric parameters and sensor calibration was performed. It is shown that this inversion technique is stable even in the presence of errors in the sensor calibration and the atmospheric parameters. The method was applied to Landsat data in two wavelengths. The results show reasonable dependence of the derived surface reflectance on the distance from the seashore.

Mekler, Y.↗

The computation of Laplacian smoothing splines with examples

Laplacian smoothing splines (LSS) are presented as generalizations of graduation, cubic and thin plate splines. The method of generalized cross validation (GCV) to choose the smoothing parameter is described. The GCV is used in the algorithm for the computation of LSS's. An outline of a computer program which implements this algorithm is presented along with a description of the use of the program. Examples in one, two and three dimensions demonstrate how to obtain estimates of function values with confidence intervals and estimates of first and second derivatives. Probability plots are used as a diagnostic tool to check for model inadequacy.

Wendelberger, J. G.↗

Mesh generation by conformal and quasiconformal mappings

It is pointed out that many recent advances in the finite-difference solution of elliptic equations have been limited to regions whose boundary contours coincide with coordinate lines of the Cartesian coordinate system. The reason for this is related to the fact that in the case of an arbitrary curvilinear coordinate system the original equation becomes much more complex. However, there is no added complexity if an orthogonal coordinate system is generated from a conformal mapping. In the present investigation, a finite difference method developed for the construction of conformal mappings has been generalized to construct quasi-conformal mappings. It is expected that the use of more sophisticated numerical algorithms could lead to improvements in both speed and accuracy. Quasi-conformal mappings have applications not only in the solution of elliptic equations but also in other areas such as orthogonal mesh generation on surfaces and the solution of certain fluid flow problems.

Mastin, C. W.↗

A fully vectorized numerical solution of the incompressible Navier-Stokes equations

A vectorizable algorithm is presented for the implicit finite difference solution of the incompressible Navier-Stokes equations in general curvilinear coordinates. The unsteady Reynolds averaged Navier-Stokes equations solved are in two dimension and non-conservative primitive variable form. A two-layer algebraic eddy viscosity turbulence model is used to incorporate the effects of turbulence. Two momentum equations and a Poisson pressure equation, which is obtained by taking the divergence of the momentum equations and satisfying the continuity equation, are solved simultaneously at each time step. An elliptic grid generation approach is used to generate a boundary conforming coordinate system about an airfoil. The governing equations are expressed in terms of the curvilinear coordinates and are solved on a uniform rectangular computational domain. A checkerboard SOR, which can effectively utilize the computer architectural concept of vector processing, is used for iterative solution of the governing equations.

Patel, N.↗

A comparison of the efficiency of numerical methods for integrating chemical kinetic rate equations

The efficiency of several algorithms used for numerical integration of stiff ordinary differential equations was compared. The methods examined included two general purpose codes EPISODE and LSODE and three codes (CHEMEQ, CREK1D and GCKP84) developed specifically to integrate chemical kinetic rate equations. The codes were applied to two test problems drawn from combustion kinetics. The comparisons show that LSODE is the fastest code available for the integration of combustion kinetic rate equations. It is shown that an iterative solution of the algebraic energy conservation equation to compute the temperature can be more efficient then evaluating the temperature by integrating its time-derivative.

Radhakrishnan, K.↗

Embedded mesh solutions of the Euler equation using a multiple-grid method

New developments make it now possible to obtain solutions to Euler equations for many problems on the basis of acceptable computing times. The possibility of an extension of these methods to more difficult flows and increasingly complex geometries can depend on obtaining suitable grid structures. Thus, an attractive approach to complex geometries involves the recasting of the problem into the framework of a multiple-grid structure. The discrete equations represented on the grid are solved as a simultaneous system. In the present investigation, this is accomplished with the aid of Ni's multiple-grid algorithm. The multiple-grid structure provided in this study represents the first step towards a completely general modular approach to the solution of the complete compressible flow problem. In the presented cases, a fine mesh resolution is obtained within the embedded mesh regions, while preserving the global coarse mesh convergence rates.

Usab, W. J., Jr.↗

Optimal guidance and propulsion control for transatmospheric vehicles

Problems associated with on-board trajectory optimization and with the synthesis of guidance laws are addressed for ascent to LEO of an air-breathing, single-stage-to-orbit vehicle. A multimode propulsion system is assumed which incorporates turbojet, ramjet, scramjet, and rocket engines. An energy-state approximation is applied to a four-state dynamic model for flight of a point mass over a spherical nonrotating earth. An algorithm for generating fuel-optimal climb profiles is derived via singular perturbation theory. This algorithm results from application of the minimum principle to a low-order dynamic model that includes general functional dependence on angle of attack and a normal component of thrust. Switching conditions are derived which, under appropriate assumptions, govern optimal transition from one propulsion mode to another. The use of bank angle to modulate the magnitude of the vertical component of lift is shown to improve the index performance. Numerical results illustrate the nature of the resulting fuel-optimal climb paths.

Corban, J. E.↗

Saberliner flight test for airborne wind shear forward looking detection and avoidance radar systems

Westinghouse conducted a flight test with its Sabreliner AN/APG-68 instrumented radar to assess the urban discrete/ground moving vehicle clutter environment. Glideslope approaches were flown into Washington National, BWI, and Georgetown, Delaware, airports employing radar mode timing, waveform, and processing configurations plausible for microburst windshear avoidance. The perceptions, both general and specific, of the clutter environment furnish an empirical foundation for beginning low false alarm detection algorithm development.

Mathews, Bruce D.↗

Interplanetary program to optimize simulated trajectories (IPOST). Volume 4: Sample cases

The Interplanetary Program to Optimize Simulated Trajectories (IPOST) is intended to support many analysis phases, from early interplanetary feasibility studies through spacecraft development and operations. The IPOST output provides information for sizing and understanding mission impacts related to propulsion, guidance, communications, sensor/actuators, payload, and other dynamic and geometric environments. IPOST models three degree of freedom trajectory events, such as launch/ascent, orbital coast, propulsive maneuvering (impulsive and finite burn), gravity assist, and atmospheric entry. Trajectory propagation is performed using a choice of Cowell, Encke, Multiconic, Onestep, or Conic methods. The user identifies a desired sequence of trajectory events, and selects which parameters are independent (controls) and dependent (targets), as well as other constraints and the cost function. Targeting and optimization are performed using the Standard NPSOL algorithm. The IPOST structure allows sub-problems within a master optimization problem to aid in the general constrained parameter optimization solution. An alternate optimization method uses implicit simulation and collocation techniques.

Hong, P. E.↗

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