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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6

Parallel Multigrid in Time and Space for Extreme-Scale Computational Science

The coming massive parallelism of exascale computing presents a pressing challenge for the many DOE simulations of time-dependent partial differential equations, which typically use traditional sequential time stepping methods. Since this traditional approach is inherently serial, it presents a sequential bottleneck when moving to exascale computing, because future performance gains will come through greater concurrency, not faster clock speeds. Thus, the goal of this work is to research parallelism in time, i.e., methods that compute multiple time values simultaneously, not sequentially. The focus will be on hyperbolic and chaotic problems of programmatic interest to DOE, with the goal of enabling scalable simulations of time-dependent hyperbolic and chaotic problems on future architectures.

97 MATHEMATICS AND COMPUTING↗

RAPID

Parallel computer code for the simulator for dynamics of power systems which has the capability to initiate the system and create different faults for the dynamic analysis. The code is based on time-parallel method (Parareal) with Adaptive Method Reduction (AMR). The coarse solvers for the Parareal algorithm include several Semi Analytical Solution methods. Also, Integrated simulation of coupled transmission and distribution systems can be studied.

Simunovic, Srdjan [Oak Ridge National Lab. (ORNL),↗

Quality of Cultural Heritage in EIA; twenty years of experience in Norway

The aim of this paper is to clarify and discuss how quality, relevance, attitudes, beliefs and transfer value act as underlying driving forces in the development of the Cultural Heritage theme in EIAs. One purpose is to identify and discuss some conditions that can better environmental assessment in order to increase the significance of EIA in decision-making with regard to Cultural Heritage. The main tools used are different research methods designed for analyses of quality and quality changes, primarily based on the relevant opinions of 160 people occupied with Cultural Heritage in EIA in Norway. The study is based on a review of 40 types of EIAs from 1991 to 2000, an online questionnaire to 319 (160 responded) individuals from 14 different backgrounds, and interviews with three institutions in Sweden and Denmark. The study confirms a steadily increasing quality on EIRs over time, parallel with an improvement of the way in which Cultural Heritage is treated in EIA. This is supported by both the interviews and the qualitative comments regarding the survey. Potential for improvements is shown to be a need for more detailed background material as well as more use of adequate methods. The survey shows the existence of a wide variety of negative views, attitudes and beliefs, but the consequences of this are difficult to evaluate. However, most certainly, negative attitudes and beliefs have not been powerful enough to be detrimental to the quality of Cultural Heritage component, as nothing in the study indicates that negative attitudes and myths are undermining the system of EIA. The study shows the importance of having on-going discussions on quality and quality change over time by people involved in EIA, and how this is a necessary condition for successful implementation and acceptance. Beliefs and negative attitudes can also be a catalyst for developing better practice and advancing new methodology. In addition, new EIA countries must be prepared for several years of development and improvements after implementation. This is important in order to gain acceptance from the bureaucracy, especially from the Cultural Heritage authorities and local population.

54 ENVIRONMENTAL SCIENCES↗

Electrophysiological interrogation of asymmetric droplet interface bilayers reveals surface-bound alamethicin induces lipid flip-flop

The droplet interface bilayer (DIB) method offers simple control over initial leaflet compositions in model membranes, enabling an experimental path to filling gaps in our knowledge about the interplay between compositional lipid asymmetry, membrane properties, and the behaviors of membrane-active species. Yet, the stability of lipid leaflet asymmetry in DIBs has received very little attention, particularly in the presence of peptides and ion channels that are often studied in DIBs. Herein, we demonstrate for the first time parallel, capacitance-based measurements of intramembrane potential with arrays of asymmetric DIBs assembled in a microfluidic device to characterize the stability of leaflet asymmetry over many hours in the presence and absence of membrane-active peptides. DIBs assembled from opposing monolayers of the ester (DPhPC) and ether (DOPhPC) forms of diphytanoyl-phosphatidylcholine yielded asymmetric bilayers with leaflet compositions that were stable for at least 18 has indicated by a stable |137 mV| intramembrane potential. In contrast, the addition of surface-bound alamethicin peptides caused a gradual, concentration-dependent decrease in the magnitude of the dipole potential difference. Intermittent current-voltage measurements revealed that alamethicin in asymmetric DIBs also shifts the threshold voltage required to drive peptide insertion and ion channel formation. These outcomes take place over the course of 1 to 5 h after membrane formation, and suggest that alamethicin peptides promote lipid flip-flop, even in the un-inserted, surface-bound state, by disordering lipids in the monolayer to which they bind. Furthermore, this methodology establishes the use of parallel electrophysiology for efficiently studying membrane asymmetry in arrays of DIBs.

59 BASIC BIOLOGICAL SCIENCES↗

Temporal parallelization of edge plasma simulations using the parareal algorithm and the SOLPS code

We show that numerical modelling of edge plasma physics may be successfully parallelized in time. The parareal algorithm has been employed for this purpose and the SOLPS code package coupling the B2.5 finite-volume fluid plasma solver with the kinetic Monte-Carlo neutral code Eirene has been used as a test bed. The complex dynamics of the plasma and neutrals in the scrape-off layer (SOL) region makes this a unique application. It is demonstrated that a significant computational gain (more than an order of magnitude) may be obtained with this technique. The use of the IPS framework for event-based parareal implementation optimizes resource utilization and has been shown to significantly contribute to the computational gain.

97 MATHEMATICS AND COMPUTING↗

A biophysical approach to the performance diagnosis of human–building energy interaction: Information (bits) modeling, algorithm, and indicators of energy flow complexity

Highlights: • Energy-related human-building interaction is analyzed at the biophysical system scale. • Energy flow-networking model of environmental building performance is suggested. • Information is suggested as a holistic building performance metric. - Abstract: This article addresses the utmost upstream impacts of human–building energy interaction by proposing a network-based model, algorithms, and indicators. Hypothesizing that human behavior is a key factor for the symbiotic development of building and the geobiosphere system, the author seeks emergy (spelled with an “m”)-information integrated measures to indicate dynamic system-level performance of the interaction with building energy flow topology. To validate the hypothesis and methods, four representative building cases were tested on the building form (envelope) of (i) a building with no occupant intervention (baseline), (ii) a building controlled by responsive human behavior (bioclimatic adaptation), (iii) a building with reinforced insulation and behavior-dominated control (passive design), and (iv) a net-zero energy building (NZEB). The results demonstrate that adaptive human behavior in building operation increases the information content and complexity of energy-flow networking, improving performance and sustainability. Findings also reveal that increasing information, complexity, and power (energy availability over time) parallel the general energetic features of developing biophysical systems (greater feedback, internalization, and recycling of materials and energies). It becames clear that active behavioral response is a dominant agent of sustainable environments even on a far broader system scale.

54 ENVIRONMENTAL SCIENCES↗

High temperature inelastic constitutive models for the ASME Section III, Division 5 Class A materials

This report describes the exploration of a universal high temperature inelastic constitutive model for use with the ASME Boiler & Pressure Vessel Code Section III, Division 5, Class A design rules. The idea, developed based on feedback from reactor vendors, is to simplify the current bespoke material models for Grade 91, 316H, and Alloy 617 and the new model for Alloy 800H into a simple, single model form. The report describes a new parallel time integration technique implemented in the pyoptmat package which allowed us to explore a wide variety of model forms, searching for a suitable common model. The report then describes preliminary work on models for monontonic deformation and then the development of a set of models suitable for capturing high temperature cyclic deformation. These models are suitable for use with the ASME design rules, except potentially for a narrow, material-specific band of temperatures at the edge of the creep regime. An incremental improvement the current models could overcome this discrepancy and provide a new, simpler set of constitutive model for all four materials.

36 MATERIALS SCIENCE↗

Optimal control system design of an acid gas removal unit for an IGCC power plants with CO2 capture

Future IGCC plants with CO{sub 2} capture should be operated optimally in the face of disturbances without violating operational and environmental constraints. To achieve this goal, a systematic approach is taken in this work to design the control system of a selective, dual-stage Selexol-based acid gas removal (AGR) unit for a commercial-scale integrated gasification combined cycle (IGCC) power plant with pre-combustion CO{sub 2} capture. The control system design is performed in two stages with the objective of minimizing the auxiliary power while satisfying operational and environmental constraints in the presence of measured and unmeasured disturbances. In the first stage of the control system design, a top-down analysis is used to analyze degrees of freedom, define an operational objective, identify important disturbances and operational/environmental constraints, and select the control variables. With the degrees of freedom, the process is optimized with relation to the operational objective at nominal operation as well as under the disturbances identified. Operational and environmental constraints active at all operations are chosen as control variables. From the results of the optimization studies, self-optimizing control variables are identified for further examination. Several methods are explored in this work for the selection of these self-optimizing control variables. Modifications made to the existing methods will be discussed in this presentation. Due to the very large number of candidate sets available for control variables and due to the complexity of the underlying optimization problem, solution of this problem is computationally expensive. For reducing the computation time, parallel computing is performed using the Distributed Computing Server (DCS®) and the Parallel Computing® toolbox from Mathworks®. The second stage is a bottom-up design of the control layers used for the operation of the process. First, the regulatory control layer is designed followed by the supervisory control layer. Finally, an optimization layer is designed. In this paper, the proposed two-stage control system design approach is applied to the AGR unit for an IGCC power plant with CO{sub 2} capture. Aspen Plus Dynamics® is used to develop the dynamic AGR process model while MATLAB is used to perform the control system design and for implementation of model predictive control (MPC).

97 MATHEMATICS AND COMPUTING↗

Sensor placement algorithm development to maximize the efficiency of acid gas removal unit for integrated gasifiction combined sycle (IGCC) power plant with CO2 capture

Future integrated gasification combined cycle (IGCC) power plants with CO{sub 2} capture will face stricter operational and environmental constraints. Accurate values of relevant states/outputs/disturbances are needed to satisfy these constraints and to maximize the operational efficiency. Unfortunately, a number of these process variables cannot be measured while a number of them can be measured, but have low precision, reliability, or signal-to-noise ratio. In this work, a sensor placement (SP) algorithm is developed for optimal selection of sensor location, number, and type that can maximize the plant efficiency and result in a desired precision of the relevant measured/unmeasured states. In this work, an SP algorithm is developed for an selective, dual-stage Selexol-based acid gas removal (AGR) unit for an IGCC plant with pre-combustion CO{sub 2} capture. A comprehensive nonlinear dynamic model of the AGR unit is developed in Aspen Plus Dynamics® (APD) and used to generate a linear state-space model that is used in the SP algorithm. The SP algorithm is developed with the assumption that an optimal Kalman filter will be implemented in the plant for state and disturbance estimation. The algorithm is developed assuming steady-state Kalman filtering and steady-state operation of the plant. The control system is considered to operate based on the estimated states and thereby, captures the effects of the SP algorithm on the overall plant efficiency. The optimization problem is solved by Genetic Algorithm (GA) considering both linear and nonlinear equality and inequality constraints. Due to the very large number of candidate sets available for sensor placement and because of the long time that it takes to solve the constrained optimization problem that includes more than 1000 states, solution of this problem is computationally expensive. For reducing the computation time, parallel computing is performed using the Distributed Computing Server (DCS®) and the Parallel Computing® toolbox from Mathworks®. In this presentation, we will share our experience in setting up parallel computing using GA in the MATLAB® environment and present the overall approach for achieving higher computational efficiency in this framework.

97 MATHEMATICS AND COMPUTING↗

Sensor placement algorithm development to maximize the efficiency of acid gas removal unit for integrated gasification combined cycle (IGCC) power plant with CO{sub 2} capture

Future integrated gasification combined cycle (IGCC) power plants with CO{sub 2} capture will face stricter operational and environmental constraints. Accurate values of relevant states/outputs/disturbances are needed to satisfy these constraints and to maximize the operational efficiency. Unfortunately, a number of these process variables cannot be measured while a number of them can be measured, but have low precision, reliability, or signal-to-noise ratio. In this work, a sensor placement (SP) algorithm is developed for optimal selection of sensor location, number, and type that can maximize the plant efficiency and result in a desired precision of the relevant measured/unmeasured states. In this work, an SP algorithm is developed for an selective, dual-stage Selexol-based acid gas removal (AGR) unit for an IGCC plant with pre-combustion CO{sub 2} capture. A comprehensive nonlinear dynamic model of the AGR unit is developed in Aspen Plus Dynamics® (APD) and used to generate a linear state-space model that is used in the SP algorithm. The SP algorithm is developed with the assumption that an optimal Kalman filter will be implemented in the plant for state and disturbance estimation. The algorithm is developed assuming steady-state Kalman filtering and steady-state operation of the plant. The control system is considered to operate based on the estimated states and thereby, captures the effects of the SP algorithm on the overall plant efficiency. The optimization problem is solved by Genetic Algorithm (GA) considering both linear and nonlinear equality and inequality constraints. Due to the very large number of candidate sets available for sensor placement and because of the long time that it takes to solve the constrained optimization problem that includes more than 1000 states, solution of this problem is computationally expensive. For reducing the computation time, parallel computing is performed using the Distributed Computing Server (DCS®) and the Parallel Computing® toolbox from Mathworks®. In this presentation, we will share our experience in setting up parallel computing using GA in the MATLAB® environment and present the overall approach for achieving higher computational efficiency in this framework.

20 FOSSIL-FUELED POWER PLANTS↗

QRCODE: Massively parallelized real-time time-dependent density functional theory for periodic systems

We present a new software module, QRCODE (Quantum Research for Calculating Optically Driven Excitations), for massively parallelized real-time time-dependent density functional theory (RT-TDDFT) calculations of periodic systems in the open-source Qbox software package. Our approach utilizes a custom implementation of a fast Fourier transformation scheme that significantly reduces inter-node message passing interface (MPI) communication of the major computational kernel and shows impressive scaling up to 16,344 CPU cores. In addition to improving computational performance, QRCODE contains a suite of various time propagators for accurate RT-TDDFT calculations. As benchmark applications of QRCODE, we calculate the current density and optical absorption spectra of hexagonal boron nitride (h-BN) and photo-driven reaction dynamics of the ozone-oxygen reaction. We also calculate the second and higher harmonic generation of monolayer and multi-layer boron nitride structures as examples of large material systems. Our optimized implementation of RT-TDDFT in QRCODE enables large-scale calculations of real-time electron dynamics of chemical and material systems with enhanced computational performance and impressive scaling across several thousand CPU cores.

97 MATHEMATICS AND COMPUTING↗

Long-time dynamics through parallel trajectory splicing

Simulating the atomistic evolution of materials over long time scales is a longstanding challenge, especially for complex systems where the distribution of barrier heights is very heterogeneous. Such systems are difficult to investigate using conventional long-time scale techniques, and the fact that they tend to remain trapped in small regions of configuration space for extended periods of time strongly limits the physical insights gained from short simulations. We introduce a novel simulation technique, Parallel Trajectory Splicing (ParSplice), that aims at addressing this problem through the timewise parallelization of long trajectories. The computational efficiency of ParSplice stems from a speculation strategy whereby predictions of the future evolution of the system are leveraged to increase the amount of work that can be concurrently performed at any one time, hence improving the scalability of the method. ParSplice is also able to accurately account for, and potentially reuse, a substantial fraction of the computational work invested in the simulation. We validate the method on a simple Ag surface system and demonstrate substantial increases in efficiency compared to previous methods. As a result, we then demonstrate the power of ParSplice through the study of topology changes in Ag 42 Cu 13 core–shell nanoparticles.

36 MATERIALS SCIENCE↗

A Performance Model for Allocating the Parallelism in a Multigrid-in-Time Solver

The traditional way to numerically solve time-dependent problems is to sequentially march through time, solving for one time step and then the next. The parallelism in this approach is limited to the spatial dimension, which is quickly exhausted, causing the gain from using more processors to solve a problem to diminish. One approach to overcome this barrier is to use methods that are parallel in time. These methods have the potential to achieve dramatically better performance compared to time-stepping approaches, but achieving this performance requires carefully choosing the amount of parallelism devoted to space versus the amount devoted to time. Here, we present a performance model that, for a multigrid-in-time solver, makes the decision on when to switch to parallel-in-time and on how much parallelism to devote to space vs. time. In our experiments, the model selects the best parallel configuration in most of our test cases and a configuration close to the best one in all other cases.

97 MATHEMATICS AND COMPUTING↗

PARLO: PArallel Run-Time Layout Optimization for Scientific Data Explorations with Heterogeneous Access Patterns

The size and scope of cutting-edge scientific simulations are growing much faster than the I/O and storage capabilities of their run-time environments. The growing gap is exacerbated by exploratory, data-intensive analytics, such as querying simulation data with multivariate, spatio-temporal constraints, which induces heterogeneous access patterns that stress the performance of the underlying storage system. Previous work addresses data layout and indexing techniques to improve query performance for a single access pattern, which is not sufficient for complex analytics jobs. We present PARLO a parallel run-time layout optimization framework, to achieve multi-level data layout optimization for scientific applications at run-time before data is written to storage. The layout schemes optimize for heterogeneous access patterns with user-specified priorities. PARLO is integrated with ADIOS, a high-performance parallel I/O middleware for large-scale HPC applications, to achieve user-transparent, light-weight layout optimization for scientific datasets. It offers simple XML-based configuration for users to achieve flexible layout optimization without the need to modify or recompile application codes. Experiments show that PARLO improves performance by 2 to 26 times for queries with heterogeneous access patterns compared to state-of-the-art scientific database management systems. Compared to traditional post-processing approaches, its underlying run-time layout optimization achieves a 56% savings in processing time and a reduction in storage overhead of up to 50%. PARLO also exhibits a low run-time resource requirement, while also limiting the performance impact on running applications to a reasonable level.

Computer Science↗

PARLO: PArallel Run-Time Layout Optimization for Scientific Data Explorations with Heterogeneous Access Pattern

Download Citation Email Print Request Permissions Save to Project The size and scope of cutting-edge scientific simulations are growing much faster than the I/O and storage capabilities of their run-time environments. The growing gap is exacerbated by exploratory, data-intensive analytics, such as querying simulation data with multivariate, spatio-temporal constraints, which induces heterogeneous access patterns that stress the performance of the underlying storage system. Previous work addresses data layout and indexing techniques to improve query performance for a single access pattern, which is not sufficient for complex analytics jobs. We present PARLO a parallel run-time layout optimization framework, to achieve multi-level data layout optimization for scientific applications at run-time before data is written to storage. The layout schemes optimize for heterogeneous access patterns with user-specified priorities. PARLO is integrated with ADIOS, a high-performance parallel I/O middleware for large-scale HPC applications, to achieve user-transparent, light-weight layout optimization for scientific datasets. It offers simple XML-based configuration for users to achieve flexible layout optimization without the need to modify or recompile application codes. Experiments show that PARLO improves performance by 2 to 26 times for queries with heterogeneous access patterns compared to state-of-the-art scientific database management systems. Compared to traditional post-processing approaches, its underlying run-time layout optimization achieves a 56% savings in processing time and a reduction in storage overhead of up to 50%. PARLO also exhibits a low run-time resource requirement, while also limiting the performance impact on running applications to a reasonable level.

Gong, Zhenhuan↗

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↗

Parallelized real-time physics codes for plasma control on DIII-D

A real-time safe multi-threading library was developed on the DIII-D plasma control system to optimize the real-time TORBEAM and real-time STRIDE physics codes. These physics codes are crucial for future fusion power plant operation as they provide information about electron cyclotron wave propagation and heating as well as inform about ideal plasma stability limits. The real-time TORBEAM code executed consistently in under 20 ms while the real-time STRIDE code computes in 100 ms. The multi-threading library developed in this work can be applied to other real-time physics-based codes that will be crucial for the next generation of fusion devices.

DIII-D↗

Space-Time Block Preconditioning for Incompressible Flow

Parallel-in-time methods have become increasingly popular in the simulation of time-dependent numerical PDEs, allowing for the efficient use of additional message passing interface processes when spatial parallelism saturates. Most methods treat the solution and parallelism in space and time separately. In contrast, all-at-once methods solve the full space-time system directly, largely treating time as simply another spatial dimension. All-at-once methods offer a number of benefits over separate treatment of space and time, most notably significantly increased parallelism and faster time to solution (when applicable). However, the development of fast, scalable all-at-once methods has largely been limited to time-dependent (advection-)diffusion problems. This paper introduces the concept of space-time block preconditioning for the all-at-once solution of incompressible flow. By extending well-known concepts of spatial block preconditioning to the space-time setting, we develop a block preconditioner whose application requires the solution of a space-time (advection-)diffusion equation in the velocity block, coupled with a pressure Schur complement approximation consisting of independent spatial solves at each time-step, and a space-time matrix-vector multiplication. The new method is tested on four classical models in incompressible flow. Finally, the results indicate perfect scalability in refinement of spatial and temporal mesh spacing, perfect scalability in nonlinear Picard iteration count when applied to a nonlinear Navier--Stokes problem, and minimal overhead in terms of number of preconditioner applications compared with sequential time-stepping.

97 MATHEMATICS AND COMPUTING↗