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At least 1,423 records · Page 79

Characterizing a Wake-Free Safe Zone for the Simplified Aircraft-Based Paired Approach Concept

The Federal Aviation Administration (FAA) has proposed a concept of operations geared towards achieving increased arrival throughput at U.S. Airports, known as the Simplified Aircraft-based Paired Approach (SAPA) concept. In this study, a preliminary characterization of a wake-free safe zone (WFSZ) for the SAPA concept has been performed. The experiment employed Monte-Carlo simulations of varying approach profiles by aircraft pairs to closely-spaced parallel runways. Three different runway lateral spacings were investigated (750 ft, 1000 ft and 1400 ft), along with no stagger and 1500 ft stagger between runway thresholds. The paired aircraft were flown in a leader/trailer configuration with potential wake encounters detected using a wake detection surface translating with the trailing aircraft. The WFSZ is characterized in terms of the smallest observed initial in-trail distance leading to a wake encounter anywhere along the approach path of the aircraft. The results suggest that the WFSZ can be characterized in terms of two primary altitude regions, in ground-effect (IGE) and out of ground-effect (OGE), with the IGE region being the limiting case with a significantly smaller WFSZ. Runway stagger was observed to only modestly reduce the WFSZ size, predominantly in the OGE region.

Guerreiro, Nelson M.↗

Pair Cascades and Deathlines in Offset Magnetic Dipole Fields

We investigate electron-positron pair cascades in a dipole magnetic field whose axis is offset from the neutron star center. In such a field geometry, the polar cap is displaced from the neutron star symmetry axis and the field line radius of curvature is modified. Using the modified parallel electric field near the polar cap of an offset dipole, we simulate pair cascades to determine the pair deathlines and pair multiplicities as a function of the offset parameter. We find that the pair multiplicity can change dramatically with a modest offset, with a significant increase on one side of the polar cap. Lower pair deathlines allow a larger fraction of the pulsar population, that include old and millisecond pulsars, to produce cascades with high multiplicity.

Harding, Alice↗

Analysis and Simulation of the Simplified Aircraft-Based Paired Approach Concept With the ALAS Alerting Algorithm in Conjunction With Echelon and Offset Strategies

This report presents analytical and simulation results of an investigation into proposed operational concepts for closely spaced parallel runways, including the Simplified Aircraft-based Paired Approach (SAPA) with alerting and an escape maneuver, MITRE?s echelon spacing and no escape maneuver, and a hybrid concept aimed at lowering the visibility minima. We found that the SAPA procedure can be used at 950 ft separations or higher with next-generation avionics and that 1150 ft separations or higher is feasible with current-rule compliant ADS-B OUT. An additional 50 ft reduction in runway separation for the SAPA procedure is possible if different glideslopes are used. For the echelon concept we determined that current generation aircraft cannot conduct paired approaches on parallel paths using echelon spacing on runways less than 1400 ft apart and next-generation aircraft will not be able to conduct paired approach on runways less than 1050 ft apart. The hybrid concept added alerting and an escape maneuver starting 1 NM from the threshold when flying the echelon concept. This combination was found to be effective, but the probability of a collision can be seriously impacted if the turn component of the escape maneuver has to be disengaged near the ground (e.g. 300 ft or below) due to airport buildings and surrounding terrain. We also found that stabilizing the approach path in the straight-in segment was only possible if the merge point was at least 1.5 to 2 NM from the threshold unless the total system error can be sufficiently constrained on the offset path and final turn.

Torres-Pomales, Wilfredo↗

Near-Body Grid Adaption for Overset Grids

A solution adaption capability for curvilinear near-body grids has been implemented in the OVERFLOW overset grid computational fluid dynamics code. The approach follows closely that used for the Cartesian off-body grids, but inserts refined grids in the computational space of original near-body grids. Refined curvilinear grids are generated using parametric cubic interpolation, with one-sided biasing based on curvature and stretching ratio of the original grid. Sensor functions, grid marking, and solution interpolation tasks are implemented in the same fashion as for off-body grids. A goal-oriented procedure, based on largest error first, is included for controlling growth rate and maximum size of the adapted grid system. The adaption process is almost entirely parallelized using MPI, resulting in a capability suitable for viscous, moving body simulations. Two- and three-dimensional examples are presented.

Buning, Pieter G.↗

A DSMC Surface Chemistry Model for Carbon-Based Ablators

A detailed molecular surface chemistry model for the DSMC (Direct Simulation Monte Carlo) method is proposed and implemented into the SPARTA (Stochastic PArallel Rarefied-gas Time-accurate Analyzer) DSMC solver. Molchanova et al. constructed a molecular model for surface recombination in DSMC that includes different surface processes (adsorption, desoprtion, Eley-Rideal and Langmuir-Hinshelwood). All surface processes can be divided into two groups: surface mechanisms, which involve only the particle adsorbed by the surface (desorption and Langmuir-Hinshelwood), and impact mechanisms, which also involve gas-phase particles (adsorption, Eley-Rideal). Using a similar approach, the 14-reaction kinetic model of oxygen-carbon interaction suggested by Zhlukhtov and Abe, as well as more recent models by Alba et al., Poovathinghal et al., and a new model developed in the scope of this work, are implemented in SPARTA. The computational results for the different oxidation models are compared with experimental results from Murray et al. (oxidation of a vitreous carbon surface due to a hyperthermal beam of O and O2), with a particular focus on fluxes, angular and Time-Of-Flight distributions of scattered particles.

oxidation↗

Protein Molecular Dynamics Simulations with Approximate QM: What Can We Learn?

Classical force fields are essential for computer simulations of proteins and are typically parameterized to reproduce secondary and tertiary structure of isolated proteins. However, while protein-protein interactions are ubiquitous in nature, they are not considered in parameterization efforts and are far less understood than isolated proteins. A better characterization of intermolecular interactions is widely recognized as a key to revolutionizing drug and therapeutic developments with high-throughput computational screening. Urgently needed is a critical assessment of the performance of modern protein force fields against first-principles electronic structure methods and experiments. In a daring step toward this goal, we here describe a comparison of peptide folding dynamics as predicted by a molecular mechanics force field on the one hand and by an approximate electronic structure quantum mechanical (QM) method based on density-functional tight-binding (DFTB) on the other. We further compare the dynamics from straightforward DFTB simulations with a near-linear scaling version of DFTB for massively parallel computation based on the fragment molecular orbital (FMO-DFTB) method. We illustrate differences between the phenomenology of the folding dynamics from these three methods for a small model peptide, as well as charge polarization and dynamic fluctuations, point out possible correlations and implications for force field developers, and discuss the lessons learned that might become applicable to future predictive high-throughput computer screening for personalized neoantigen cancer therapy.

Irle, Stephan↗

Toward designing effective exascale scientific computing workflows: experiences and best practices

Many fields within scientific computing have embraced advances in big-data analysis and machine learning, which often requires the deployment of large, distributed and complicated workflows that may combine training neural networks, performing simulations, running inference, and performing database queries and data analysis in asynchronous, parallel and pipelined execution frameworks. Such a shift has brought into focus the need for scalable, efficient workflow management solutions with reproducibility, error and provenance handling, traceability, and checkpoint-restart capabilities, among other needs. Here, we discuss challenges and best-practices for deploying exascale-generation computational science workflows on resources at the Oak Ridge Leadership Computing Facility (OLCF). We present our experiences with large-scale deployment of distributed workflows on the Summit supercomputer, including for bioinformatics and computational biophysics, materials science, and deep learning model optimization. We also present problems and solutions created by working within a Python-centric software base on traditional HPC systems, and discuss steps that will be required before the convergence of HPC, AI, and data science can be fully realized. Our results point to a wealth of exciting new possibilities for harnessing this convergence to tackle new scientific challenges.

Coletti, Mark↗

Data-Driven Unit Commitment Refinement - a Scalable Approach for Complex Modern Power Grids

Integration of renewable generation, which is often intermittent and decentralized, substantially increases the stochasticity and complexity of power grid operations. Future power systems planning will require significant computational capability to evaluate balance between demand and supply under varying conditions, both temporally and spatially. The standard approach for generation unit commitment is to use mixed-integer linear programming to find the optimal generation schedule considering ramping and generator constraints. In the future grid this poses computational scalability challenges because generation and demand are not known with certainty due to stochasticity in weather and complexity of the grid. To address this challenge, we present a data-driven unit commitment approach that can efficiently include stochastic weather impacts and contingency considerations to improve unit commitment. Our approach uses graph-based data analytics techniques on solutions to the security constrained (and possibly stochastic) economic dispatch problem to identify potential improvements to a given unit commitment. Recent breakthroughs in fully-parallel stochastic economic dispatch software allow this approach to be scalably deployed. Simulations on synthetic South Carolina and Texas grids show this method can improve grid reliability with security constraints over a set of contingencies, while also meaningfully lowering total generation cost.

Holt, Timothy↗

Simulation and control of a 20 kHz spacecraft power system

A detailed computer representation of four Mapham inverters connected in a series, parallel arrangement has been implemented. System performance is illustrated by computer traces for the four Mapham inverters connected to a Litz cable with parallel resistance and dc receiver loads at the receiving end of the transmission cable. Methods of voltage control and load sharing between the inverters are demonstrated. Also, the detailed computer representation is used to design and to demonstrate the advantages of a feed-forward voltage control strategy. It is illustrated that with a computer simulation of this type, the performance and control of spacecraft power systems may be investigated with relative ease and facility.

Wasynczuk, O.↗

Fast Particle Methods for Multiscale Phenomena Simulations

We are developing particle methods oriented at improving computational modeling capabilities of multiscale physical phenomena in : (i) high Reynolds number unsteady vortical flows, (ii) particle laden and interfacial flows, (iii)molecular dynamics studies of nanoscale droplets and studies of the structure, functions, and evolution of the earliest living cell. The unifying computational approach involves particle methods implemented in parallel computer architectures. The inherent adaptivity, robustness and efficiency of particle methods makes them a multidisciplinary computational tool capable of bridging the gap of micro-scale and continuum flow simulations. Using efficient tree data structures, multipole expansion algorithms, and improved particle-grid interpolation, particle methods allow for simulations using millions of computational elements, making possible the resolution of a wide range of length and time scales of these important physical phenomena.The current challenges in these simulations are in : [i] the proper formulation of particle methods in the molecular and continuous level for the discretization of the governing equations [ii] the resolution of the wide range of time and length scales governing the phenomena under investigation. [iii] the minimization of numerical artifacts that may interfere with the physics of the systems under consideration. [iv] the parallelization of processes such as tree traversal and grid-particle interpolations We are conducting simulations using vortex methods, molecular dynamics and smooth particle hydrodynamics, exploiting their unifying concepts such as : the solution of the N-body problem in parallel computers, highly accurate particle-particle and grid-particle interpolations, parallel FFT's and the formulation of processes such as diffusion in the context of particle methods. This approach enables us to transcend among seemingly unrelated areas of research.

Koumoutsakos, P.↗

Temporal Precedence Checking for Switched Models and its Application to a Parallel Landing Protocol

This paper presents an algorithm for checking temporal precedence properties of nonlinear switched systems. This class of properties subsume bounded safety and capture requirements about visiting a sequence of predicates within given time intervals. The algorithm handles nonlinear predicates that arise from dynamics-based predictions used in alerting protocols for state-of-the-art transportation systems. It is sound and complete for nonlinear switch systems that robustly satisfy the given property. The algorithm is implemented in the Compare Execute Check Engine (C2E2) using validated simulations. As a case study, a simplified model of an alerting system for closely spaced parallel runways is considered. The proposed approach is applied to this model to check safety properties of the alerting logic for different operating conditions such as initial velocities, bank angles, aircraft longitudinal separation, and runway separation.

Duggirala, Parasara Sridhar↗

Importance of the Annual Cycles of SST and Solar Irradiance for Circulation and Rainfall: A Climate Model Simulation Study

Annual cycle of climate and precipitation is related to annual cycle of sunshine and sea-surface temperatures. Understanding its behavior is important for the welfare of humans worldwide. For example, failure of Asian monsoons can cause widespread famine and grave economic disaster in the subtropical regions. For centuries meteorologists have struggled to understand the importance of the summer sunshine and associated heating and the annual cycle of sea-surface temperatures (SSTs) on rainfall in the subtropics. Because the solar income is pretty steady from year to year, while SSTs depict large interannual variability as consequence of the variability of ocean dynamics, the influence of SSTs on the monsoons are better understood through observational and modeling studies whereas the relationship of annual rainfall to sunshine remains elusive. However, using NASA's state of the art climate model(s) that can generate realistic climate in a computer simulation, one can answer such questions. We asked the question: if there was no annual cycle of the sunshine (and its associated land-heating) or the SST and its associated influence on global circulation, what will happen to the annual cycle of monsoon rains? By comparing the simulation of a 4-year integration of a baseline Control case with two parallel anomaly experiments: 1) with annual mean solar and 2) with annual mean sea-surface temperatures, we were able to draw the following conclusions: (1) Tropical convergence zone and rainfall which moves with the Sun into the northern and southern hemispheres, specifically over the Indian, African, South American and Australian regions, is strongly modulated by the annual cycles of SSTs as well as solar forcings. The influence of the annual cycle of solar heating over land, however, is much stronger than the corresponding SST influence for almost all regions, particularly the subtropics; (2) The seasonal circulation patterns over the vast land-masses of the Northern Hemisphere at mid and high latitudes also get strongly influenced by the annual cycles of solar heating. The SST influence is largely limited to the oceanic regions of these latitudes; (3) The annual mode of precipitation over Amazonia has an equatorial regime revealing a maxima in the month of March associated with SST, and another maxima in the month of January associated with the solar annual cycles, respectively. The baseline simulation, which has both annual cycles, depicts both annual modes and its rainfall is virtually equal to the sum of those two modes; (4) Rainfall over Sahelian-Africa is significantly reduced (increased) in simulations lacking (invoking) solar irradiation with (without) the annual cycle. In fact, the dominant influence of solar irradiation emerges in almost all monsoonal-land regions: India, Southeast Asia, as well as Australia. The only exception is the Continental United States, where solar annual cycle shows only a relatively minor influence on the annual mode of rainfall.

Sud, Yogesh C.↗

Predicting Execution Times for Disk-based and In-Situ Parallel Data Analytics (Final Technical Report)

In recent years, there has been a significant amount of interests in in-situ analytics on simulation programs. For a variety of reasons, it is desirable to be able to predict the execution time of an analytics program. At the same time, frameworks such as MapReduce have become popular for scientific data analytics. This paper focuses on developing performance models for predicting execution time of parallel data analytics, with a special emphasis on in-situ analytics. We take two distinct approach towards performance prediction. We first expand SKOPE (a SKeleton framewOrk for Performance Exploration) with performance models for disk data read, cache performance, and page fault penalty. Second, an analytical performance model is also developed. We have evaluated our performance prediction framework as well as the analytical model on three hardware setups with well-known data mining algorithms implemented in three programming paradigms, MapReduce, MATE (a MapReduce-like parallel system with an alternate API for multi-core environments) and Smart (a MapReduce-like framework for in-situ analytics). Results show that our performance prediction framework along with the incorporated performance models are capable of accurately predicting execution times for parallel scientific analytics on different hardware setups.

97 MATHEMATICS AND COMPUTING↗

Advanced Shuttle Strategies for Parallel QCCD Architectures

Trapped ions (TIs) are at the forefront of quantum computing implementation, offering unparalleled coherence, fidelity, and connectivity. However, the scalability of TI systems is hampered by the limited capacity of individual ion traps, necessitating intricate ion shuttling for advanced computational tasks. The quantum charge-coupled device (QCCD) framework has emerged as a promising solution, facilitating ion mobility for universal quantum computation. Current QCCD architectures predominantly feature a linear topology, which is increasingly recognized as inefficient for complex quantum operations. Anticipating the shift toward more efficacious designs, this article introduces an innovative quantum scheduling strategy optimized for parallel QCCD topologies. Our strategy proposes a probabilistic formula for ion movement, alongside ingenious methods for local layer generation and layer compression, yielding a significant reduction in ion shuttle times. Through simulations, we demonstrate that our strategy not only substantially outstrips the linear model but also exhibits better performance over other parallel strategies that employ greedy algorithms. This is achieved through our nuanced resolution of complexities, such as traffic blocks and trap capacity limitations. The consequent reduction in shuttle operations leads to lower energy consumption and an enhancement in the quantum computer's fidelity, ultimately accelerating program execution times.

43 PARTICLE ACCELERATORS↗

Applications Performance Under MPL and MPI on NAS IBM SP2

On July 5, 1994, an IBM Scalable POWER parallel System (IBM SP2) with 64 nodes, was installed at the Numerical Aerodynamic Simulation (NAS) Facility Each node of NAS IBM SP2 is a "wide node" consisting of a RISC 6000/590 workstation module with a clock of 66.5 MHz which can perform four floating point operations per clock with a peak performance of 266 Mflop/s. By the end of 1994, 64 nodes of IBM SP2 will be upgraded to 160 nodes with a peak performance of 42.5 Gflop/s. An overview of the IBM SP2 hardware is presented. The basic understanding of architectural details of RS 6000/590 will help application scientists the porting, optimizing, and tuning of codes from other machines such as the CRAY C90 and the Paragon to the NAS SP2. Optimization techniques such as quad-word loading, effective utilization of two floating point units, and data cache optimization of RS 6000/590 is illustrated, with examples giving performance gains at each optimization step. The conversion of codes using Intel's message passing library NX to codes using native Message Passing Library (MPL) and the Message Passing Interface (NMI) library available on the IBM SP2 is illustrated. In particular, we will present the performance of Fast Fourier Transform (FFT) kernel from NAS Parallel Benchmarks (NPB) under MPL and MPI. We have also optimized some of Fortran BLAS 2 and BLAS 3 routines, e.g., the optimized Fortran DAXPY runs at 175 Mflop/s and optimized Fortran DGEMM runs at 230 Mflop/s per node. The performance of the NPB (Class B) on the IBM SP2 is compared with the CRAY C90, Intel Paragon, TMC CM-5E, and the CRAY T3D.

Saini, Subhash↗

The Impact of the Atlantic Cold Tongue on West African Monsoon Onset in Regional Model Simulations for 1998-2002

The Atlantic cold tongue (ACT) develops during spring and early summer near the Equator in the Eastern Atlantic Ocean and Gulf of Guinea. The hypothesis that the ACT accelerates the timing of West African monsoon (WAM) onset is tested by comparing two regional climate model (RM3) simulation ensembles. Observed sea surface temperatures (SST) that include the ACT are used to force a control ensemble. An idealized, warm SST perturbation is designed to represent lower boundary forcing without the ACT for the experiment ensemble. Summer simulations forced by observed SST and reanalysis boundary conditions for each of five consecutive years are compared to five parallel runs forced by SST with the warm perturbation. The article summarizes the sequence of events leading to the onset of the WAM in the Sahel region. The representation of WAM onset in RM3 simulations is examined and compared to Tropical Rainfall Measuring Mission (TRMM), Global Precipitation Climatology Project (GPCP) and reanalysis data. The study evaluates the sensitivity of WAM onset indicators to the presence of the ACT by analysing the differences between the two simulation ensembles. Results show that the timing of major rainfall events and therefore theWAM onset in the Sahel are not sensitive to the presence of the ACT. However, the warm SST perturbation does increase downstream rainfall rates over West Africa as a consequence of enhanced specific humidity and enhanced northward moisture flux in the lower troposphere.

Regional model simulation↗

Physical Processes for Driving Ionospheric Outflows in Global Simulations

We review and assess the importance of processes thought to drive ionospheric outflows, linking them as appropriate to the solar wind and interplanetary magnetic field, and to the spatial and temporal distribution of their magnetospheric internal responses. These begin with the diffuse effects of photoionization and thermal equilibrium of the ionospheric topside, enhancing Jeans' escape, with ambipolar diffusion and acceleration. Auroral outflows begin with dayside reconnexion and resultant field-aligned currents and driven convection. These produce plasmaspheric plumes, collisional heating and wave-particle interactions, centrifugal acceleration, and auroral acceleration by parallel electric fields, including enhanced ambipolar fields from electron heating by precipitating particles. Observations and simulations show that solar wind energy dissipation into the atmosphere is concentrated by the geomagnetic field into auroral regions with an amplification factor of 10-100, enhancing heavy species plasma and gas escape from gravity, and providing more current carrying capacity. Internal plasmas thus enable electromagnetic driving via coupling to the plasma, neutral gas and by extension, the entire body " We assess the Importance of each of these processes in terms of local escape flux production as well as global outflow, and suggest methods for their implementation within multispecies global simulation codes. We complete 'he survey with an assessment of outstanding obstacles to this objective.

Moore, Thomas Earle↗

Progress on Optimizing Wind Farms and Rotor Designs Using Adjoints

Modern wind plants are increasingly tasked with multiple performance objectives. In addition to designing plants that maximize power output and minimize the levelized cost of energy (LCOE), the design and operation of wind plants is increasingly influenced by challenges regarding grid integration of variable generation renewables. This places a growing emphasis on making wind plants more controllable and predictable. WindSE is a Reynolds-averaged Navier-Stokes (RANS) model designed around analytical gradient and adjoint methods, with the ability to capture terrain-induced effects, as shown in Figure 1. The recent addition of an unsteady solver with an actuator line method (ALM) and ongoing work to enable massively parallel optimizations gives it a unique niche to explore coupled plant-level controls and design problems. This code is an open source python package built on the FEniCS framework that utilizes fast, parallel PETSc solvers to model fluid flow throughout wind-farm scale domains. Two recent studies performed using WindSE demonstrate the capability to optimize under a wide variety of flow conditions and objective functions. In the first, we present an optimization focused on modifying the layout of a wind farm with a fixed number of turbines for maximum total power output [1]. This study highlights the ability to quickly perform simulations using the steady Navier-Stokes solver combined with rotors represented as actuator disks while also stressing the importance of capturing terrain-induced effects. Gradient-based optimization using the RANS equations is viable due to the inclusion of efficiently computed adjoint derivatives. We interpret the physical results of the optimal layout and also discuss the computational cost of scaling to larger problems. In the second study, we present the capabilities of the unsteady Navier-Stokes solver, where rotor-blade profiles represented by actuator lines are optimized to enhance wake steering effects and overall power production [2]. We quantify the wind plant performance gains obtained from this type of simultaneous control co-design optimization as compared to optimizing the blade design and yaw independently. Figure 2 shows the differences between a baseline two-turbine system and an optimized system where we fine-tune the blade chord profile. Results and challenges from each study are quickly summarized and used to motivate the current development efforts within WindSE. Current and future work is focused on enabling higher-resolution studies with more degrees of freedom through parallelization of both the simulation and optimization algorithms. We present benchmarking results to show that WindSE performs well in both weak- and strong-scaling tests and further demonstrate that the optimizer obtains the same convergence rates in both shared- and distributed-memory environments. Using larger wind farms, we can study deep-array effects within an optimization context, allowing the use of objective functions that have been previously unstudied. As an example, we present ongoing work on a blockage metric which characterizes the loss of available kinetic energy due to wake effects from multiple upstream turbines.

adjoint optimization↗