Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “solution multiplicity”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,423 records · Page 79

Solution Concepts for Distributed Decision-Making without Coordination

Consider a single-stage problem in which we have a group N agents who are attempting to minimize the expected cost of their joint actions, without the benefit of communication or a pre-established protocol but with complete knowledge of the expected cost of any joint set of actions for the group. We call this situation a static coordination problem. The central issue in defining an appropriate solution concept for static coordination problems is considering how to deal with the fact that if the agents axe faced with a set of multiple (mixed) strategies that are equally attractive in terms of cost, a failure of coordination may lead to an expected cost value that is worse than that of any of the strategies in the set. In this proposal, we describe the notion of a general coordination problem, describe initial efforts at developing a solution concept for static coordination problems, and then outline a research agenda that centers on activities that will be basis for obtaining a complete understanding of solutions to static coordination problems.

Beling, Peter A.↗

Uptake of Organic Vapors by Sulfate Aerosols: Physical and Chemical Processes

While it is known that upper tropospheric sulfate particles contain a significant amount of organic matter, both the source of the organic fraction and its form in solution are unknown. These studies explore how the chemical characteristics of the molecules and surfaces in question affect heterogeneous interactions. The solubilities of acetaldehyde [CH3CHO] and ethanol [CH3CH20H] in cold, aqueous sulfuric acid solutions have been measured by Knudsen cell studies. Henry's law solubility coefficients range from 10(exp 2) to 10(exp 5) M/atm for acetaldehyde, and from 10(exp 4) to 10(exp 9) M/atm for ethanol under upper tropospheric conditions (210-240 K, 40-80 wt. % H2S04). The multiple solvation pathways (protonation, enolization, etc.) available to these compounds in acidic aqueous environments will be discussed. Preliminary results from the interaction of acetaldehyde with solutions of formaldehyde in sulfuric acid will be presented as well. The physical and chemical processes that affect organic uptake by aqueous aerosols will be explored, with the aim of evaluating organic species not yet studied in low temperature aqueous sulfuric acid.

Michelsen, R. R.↗

DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms

Effective patient care mandates rapid, yet accurate, diagnosis. With the abundance of non-invasive diagnostic measurements and electronic health records (EHR), manual interpretation for differential diagnosis has become time-consuming and challenging. This has led to wide-spread adoption of AI-powered tools, in pursuit of improving accuracy and efficiency of this process. While the unique challenges presented by each modality and clinical task demand customized tools, the cumbersome process of making problem-specific choices has triggered the critical need for a generic solution to enable rapid development of models in practice. In this spirit, we develop DDxNet, a deep architecture for time-varying clinical data, which we demonstrate to be well-suited for diagnostic tasks involving different modalities (ECG/EEG/EHR), required level of characterization (abnormality detection/phenotyping) and data fidelity (single-lead ECG/22-channel EEG). Using multiple benchmark problems, we show that DDxNet produces high-fidelity predictive models, and sometimes even provides significant performance gains over problem-specific solutions.

60 APPLIED LIFE SCIENCES↗

Retrieval of Atmospheric and Surface Parameters from AIRS/AMSU/HSB Data Under Cloudy Conditions

New state of the art methodology is described to analyze AIRS/AMSU/HSB data in the presence of multiple cloud formations. The methodology forms the basis for the AIRS Science Team algorithm which will be used to analyze AIRS/AMSU/HSB data on EOS Aqua. The cloud clearing methodology requires no knowledge of the spectral properties of the clouds. The basic retrieval methodology is general and extracts the maximum information from the radiances, consistent with the channel noise covariance matrix. The retrieval methodology minimizes the dependence of the solution on the first guess field and the first guess error characteristics. Results are shown for AIRS Science Team simulation studies with multiple cloud formations. These simulation studies imply that clear column radiances can be reconstructed under partial cloud cover with an accuracy comparable to single spot channel noise in the temperature and water vapor sounding regions, temperature soundings can be produced under partial cloud cover with RMS errors on the order of, or better than, 1deg K in 1 km thick layers from the surface to 700 mb, 1 km layers from 700 mb to 300 mb, 3 km layers from 300 mb to 30 mb, and 5 km layers from 30 mb to 1 mb, and moisture profiles can be obtained with an accuracy better than 20% absolute errors in 1 km layers from the surface to nearly 200 mb.

Susskind, Joel↗

Rapid QSTS Simulations for High-Resolution Comprehensive Assessment of Distributed PV

The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modeling and impact analysis. Unlike conventional scenario-based studies, quasi-static time-series (QSTS) simulations can realistically model time-dependent voltage controllers and the diversity of potential impacts that can occur at different times of year. However, to accurately model a distribution system with all its controllable devices, a yearlong simulation at 1-second resolution is often required, which could take conventional computers a computational time of 10 to 120 hours when an actual unbalanced distribution feeder is modeled. This computational burden is a clear limitation to the adoption of QSTS simulations in interconnection studies and for determining optimal control solutions for utility operations. The solutions we developed include accurate and computationally efficient QSTS methods that could be implemented in existing open-source and commercial software used by utilities and the development of methods to create high-resolution proxy data sets. This project demonstrated multiple pathways for speeding up the QSTS computation using new and innovative methods for advanced time-series analysis, faster power flow solvers, parallel processing of power flow solutions and circuit reduction. The target performance level for this project was achieved with year-long high-resolution time series solutions run in less than 5 minutes within an acceptable error.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Instability saturation by the oscillating two-stream instability in a weakly relativistic plasma

The two-stream instability has wide range of astrophysical applications starting from gamma-ray bursts and pulsar glitches to cosmology. We consider one dimensional weakly relativistic Zakharov equations and describe nonlinear saturation of the oscillating two-stream instability using a three dimensional dynamical system resulting form a truncation of the nonlinear Schrodinger equation to three modes. The equilibrium points of the model are determined and their stability natures are discussed. Using the tools of nonlinear dynamics such as the bifurcation diagram, Poincaré maps, and Lyapunav exponents, existence of periodic, quasi-periodic, and chaotic solutions are established in the dynamical system. Interestingly, we observe the multistable behavior in this plasma model. The system has multiple attractors depending on the initial conditions. We also notice that the relativistic parameter plays the role of control parameter in the model. The theoretical results presented in this paper may be helpful for better understanding of space and astrophysical plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Research on Phase Reaction of Nb{sub 3}Al Precursor During Rapid Heating Process

Short samples of Nb{sub 3}Al precursor are heated by Ohm heating. The curves of temperature vs heating time are investigated to study the phase reaction of jelly-roll precursor and in situ powder-in-tube precursor during the rapid heating process. A short constant temperature process occurs at about 2000 {sup ∘}C. It is proved that the reaction that generates body-centered cubic (BCC) solid solution phase is reversible. For jelly-roll precursor, metallographic images show that no reaction occurs between Nb/Al roll and Nb matrix. Voids and cracks become larger as the precursor is processed for multiple times. For in situ powder-in-tube precursor, Nb and Al powder is not reacted completely. Using smaller original Nb powder and Al powder is good for the formation of BCC solid solution.

36 MATERIALS SCIENCE↗

RedOx-controlled sorption of iodine anions by hydrotalcite composites

The radioactive contaminant iodine-129 (I-129) is one of the top risk drivers at radiological waste disposal and contaminated groundwater sites where nuclear material fabrication or reprocessing has occurred. Currently there are very few options available to treat I-129 in the groundwater, which is partially related to its complex biogeochemical behavior in the subsurface and occurrence in the multiple chemical forms. We hypothesize that layered hydrotalcite materials containing redox active transition metal ions offer a potential solution, benefiting from the simultaneous adsorption of iodate (IO3-) and iodide (I-) anions, which exhibit different electronic and structural properties and therefore may require dissimilar hosts. To test this hypothesis, Cr3+- based materials were selected based on the rationale that Cr3+ readily reduces IO3- in solution. It was combined with either redox-active Co2+ or redox-inactive Ni2+ so that two model materials were prepared by hydrothermal synthesis including Co2+-Cr3+ and Ni2+-Cr3+(M-Cr). Obtained M-Cr materials comprised of Co2+-Cr3+ or Ni2+-Cr3+ layered hydrotalcite and small fractions of Co3O4 spinel or Ni(OH)2 theophrastite phases were structurally characterized before and after uptake of periodate (IO4-), IO3-, and I- anions. It was found that the IO3- uptake is driven by its chemical reduction to I2 and I-. Interestingly, in the Co2+-Cr3+ hydrotalcite, Co2+ and not Cr3+ serves as a reductant while in the Ni2+-Cr3+ hydrotalcite Cr3+ is responsible for the reduction of IO3-. A different uptake mechanism was identified for the IO4- anion. The Co2+-Cr3+ hydrotalcite phase efficiently uptakes IO4- by a diffusion-limited ion exchange mechanism and is not accompanied by the redox process, while Cr3+ in the Ni2+-Cr3+ hydrotalcite reduces IO4- to IO3-, I2 and I-. Iodide exhibited high affinity only to the Co-Cr material. The Co-Cr material performed remarkably well for the removal of IO3-, I- and total iodine from the groundwater collected from the US DOE Hanford site, WA, USA outperforming non-redox active hydrotalcites (e.g., Mg2+-Al3+) reported previously. This work demonstrates that redox-controlled sorption can be a highly effective method for the treatment of anions based on elements with mobile oxidation states. Further, multiple anions of interest could be simultaneously removed through combination of approaches.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Spectral convergence of the stochastic galerkin approximation to the boltzmann equation with multiple scales and large random perturbation in the collision kernel

In a 2018 article, spectral convergence and long-time decay of the numerical solution towards the global equilibrium of the stochastic Galerkin approximation for the Boltzmann equation with random inputs in the initial data and collision kernel for hard potentials and Maxwellian molecules under Grad's angular cutoff were established using the hypocoercive properties of the collisional kinetic model. One assumption for the random perturbation of the collision kernel is that the perturbation is in the order of the Knudsen number, which can be very small in the fluid dynamical regime. In this article, we remove this smallness assumption, and establish the same results but now for random perturbations of the collision kernel that can be of order one. The new analysis relies on the establishment of a spectral gap for the numerical collision operator.

97 MATHEMATICS AND COMPUTING↗

Development and Implementation of an Optimization Model for Hydropower and Total Dissolved Gas in the Mid-Columbia River System

Managing energy, water, and environmental priorities and constraints within a cascade hydropower system is a challenging multiobjective optimization effort that requires advanced modeling and forecasting tools. Within the mid-Columbia River system, there is currently a lack of specific solutions for predicting how coordinated operational decisions can mitigate the impacts of total dissolved gas (TDG) supersaturation while satisfying multiple additional policy and hydropower generation objectives. In this study, a reduced-order TDG uptake equation is developed that predicts tailrace TDG at seven hydropower facilities on the mid-Columbia River. The equation is incorporated into a general multiobjective river, reservoir, and hydropower optimization tool as a prioritized operating goal within a broader set of system-level objectives and constraints. A test case is presented to assess the response of TDG and hydropower generation when TDG supersaturation is optimized to remain under state water-quality standards. Satisfaction of TDG as an operating goal is highly dependent on whether constraints that limit TDG uptake are implemented at a higher priority than generation requests. According to the model, an opportunity exists to reduce TDG supersaturation and meet hydropower generation requirements by shifting spillway flows to different time periods. In conclusion, a coordinated effort between all project owners is required to implement systemwide optimized solutions that satisfy the operating policies of all stakeholders.

13 HYDRO ENERGY↗

Implementation of a Multichannel Serial Data Streaming Algorithm using the Xilinx Serial RapidIO Solution

In the current world of applications that use reconfigurable technology implemented on field programmable gate arrays (FPGAs), there is a need for flexible architectures that can grow as the systems evolve. A project has limited resources and a fixed set of requirements that development efforts are tasked to meet. Designers must develop robust solutions that practically meet the current customer demands and also have the ability to grow for future performance. This paper describes the development of a high speed serial data streaming algorithm that allows for transmission of multiple data channels over a single serial link. The technique has the ability to change to meet new applications developed for future design considerations. This approach uses the Xilinx Serial RapidIO LOGICORE Solution to implement a flexible infrastructure to meet the current project requirements with the ability to adapt future system designs.

RapidIO↗

Fast synchronization-free algorithms for parallel sparse triangular solves with multiple right-hand sides

The sparse triangular solve kernels, SpTRSV and SpTRSM, are important building blocks for a number of numerical linear algebra routines. Parallelizing SpTRSV and SpTRSM on today's many-core platforms, such as GPUs, is not an easy task since computing a component of the solution may depend on previously computed components, enforcing a degree of sequential processing. As a consequence, most existing work introduces a preprocessing stage to partition the components into a group of level-sets or colour-sets so that components within a set are independent and can be processed simultaneously during the subsequent solution stage. However, this class of methods requires a long preprocessing time as well as significant runtime synchronization over-heads between the sets. To address this, we

HPC↗

Single and multiple scattering contributions to circumsolar radiation

The contributions to the angular distribution of the almucantar radiance in the forward direction due to multiple scattering are compared to those due to single scattering. The contributions have been calculated by a computer code employing the Gauss-Seidel iterative approach to the solution of the radiative transfer equation for a plane parallel atmosphere composed of air molecules, aerosol particles, and ozone. The code is similar to that of Dave (1972) except in the construction of the source matrix. In the near-forward direction the multiple scattering contributions are significant for optical depths of the order of 0.4. The shape of the angular distribution of almucantar radiance to 10 degrees is less sensitive to multiple scattering.

Box, M. A.↗

Achieving dependability throughout the development process - A distributed software experiment

Distributed software engineering techniques and methods for improving the specification and testing phases are considered. With multiversion development, multiple implementations allow the use of an automated approach to testing called back-to-back (B/B) testing in which the outputs are compared to detect any discrepancies. However, a specification defect may lead to similar errors in the multiple versions and the underlying fault may not be detected with a B/B testing approach. The use of diverse formal specifications has been proposed as a solution to this problem, since defects in independently written specifications are likely to be different. To examine these issues, an experiment was performed using the design diversity approach in the specification, design, implementation, and testing of distributed software. In the experiment, three diverse formal specifications were used to produce multiple independent implementations of a distributed communication protocol in Ada. The problems encountered in building complex concurrent processing systems in Ada were also studied. Many pitfalls were discovered in mapping the formal specifications into Ada implementations.

Kelly, John P. J.↗

A UPC++ Actor Library and Its Evaluation On a Shallow Water Proxy Application

Programmability is one of the key challenges of Exascale Computing. Using the actor model for distributed computations may be one solution. The actor model separates computation from communication while still enabling their overlap. Each actor possesses specified communication endpoints to publish and receive information. Computations are undertaken based on the data available on these channels. We present a library that implements this programming model using UPC++, a PGAS library, and evaluate three different parallelization strategies, one based on rank-sequential execution, one based on multiple threads in a rank, and one based on OpenMP tasks. In an evaluation of our library using shallow water proxy applications, our solution compares favorably against an earlier implementation based on X10, and a BSP-based approach.

Pöppl, Alexander↗

Structural diversity in the Mycobacteria DUF3349 superfamily

A protein superfamily with a “Domain of Unknown Function,”, DUF3349 (PF11829), is present predominately in Mycobacterium and Rhodococcus bacterial species suggesting that these proteins may have a biological function unique to these bacteria. We previously reported the inaugural structure of a DUF3349 superfamily member, Mycobacterium tuberculosis Rv0543c. In this study, we report the structures determined for three additional DUF3349 proteins: Mycobacterium smegmatis MSMEG_1063 and MSMEG_1066 and Mycobacterium abscessus MAB_3403c. Like Rv0543c, the NMR solution structure of MSMEG_1063 revealed a monomeric five α-helix bundle with a similar overall topology. Conversely, the crystal structure of MSMEG_1066 revealed a five α-helix protein with a strikingly different topology and a tetrameric quaternary structure that was confirmed by size exclusion chromatography. The NMR solution structure of a fourth member of the DUF3349 superfamily, MAB_3403c, with 18 residues missing at the N-terminus, revealed a monomeric α-helical protein with a folding topology similar to the three C-terminal helices in the protomer of the MSMEG_1066 tetramer. These structures, together with a GREMLIN-based bioinformatics analysis of the DUF3349 primary amino acid sequences, suggest two subfamilies within the DUF3349 family. The division of the DUF3349 into two distinct subfamilies would have been lost if structure solution had stopped with the first structure in the DUF3349 family, highlighting the insights generated by solving multiple structures within a protein superfamily. Future studies will determine if the structural diversity at the tertiary and quaternary levels in the DUF3349 protein superfamily have functional roles in Mycobacteria and Rhodococcus species with potential implications for structure-based drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗

Parallel-in-Time Solution of Allen-Cahn Equations by Integrating Operator Learning into the Parareal Method

While recent advances in deep learning have shown promising efficiency gains in solving time-dependent partial differential equations (PDEs), matching the accuracy of conventional numerical solvers still remains a challenge. One strategy to improve the accuracy of deep learning-based solutions for time-dependent PDEs is to use the learned model as the coarse propagator in the Parareal method and a traditional numerical method as the fine solver. However, successful integration of deep learning into the Parareal method requires consistency between the coarse and fine solvers, particularly for PDEs exhibiting rapid changes such as sharp transitions. Here, to ensure this consistency, we propose using convolutional neural networks (CNNs) to learn the fully discrete time-stepping operator defined by the same numerical scheme employed as the fine solver. We demonstrate the effectiveness of the proposed method in solving the classical and mass-conservative Allen–Cahn (AC) equations. Through iterative updates in the Parareal algorithm, our approach achieves a significant computational speedup compared to traditional fine solvers while converging to high-accuracy solutions. Our results highlight that the proposed hybrid Parareal algorithm effectively accelerates simulations, particularly when implemented on multiple GPUs, and converges to the desired accuracy in only a few iterations. Another advantage of our method is that the CNN model is trained on trajectory-based data generated from random initial conditions, such that the trained model can be used to solve the AC equations with various initial conditions without retraining. This work demonstrates the potential of integrating neural network methods into parallel-in-time frameworks for efficient and accurate simulations of time-dependent PDEs.

97 MATHEMATICS AND COMPUTING↗