Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “distributed processing”

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 235 records · Page 13

Cross-Scale Land-Atmosphere Experiment (CSLAEX) (Final Report)

It is now well recognized that land-atmosphere interactions play an important role in both weather and climate. These interactions take place over a wide range of spatial and temporal scales. Most of the current formulations of the momentum, heat and moisture transport laws are informed by observations with a limited temporal or spatial scale, and hence may have limited applicability. The objective of this work is to improve the multi-scale representation of the near-surface heat transfer in the ground and in the atmosphere using a combination of modeling and field observations. Our knowledge and predictive capacity in land-atmosphere coupling is limited by our capacity to observe the full-scale spectrum at play. In order to bridge this fundamental gap in our observation capacity I will work to: create the first long-term Integrated Cross-Scale land-Atmosphere Experiment (CSLAEX) since I will work to: measure the components of the surface energy balance at a spatial scale relevant to remote sensing and meteorological applications (5km), along with observations of the nested subscale processes with Distributed Temperature Sensors (DTS). This proposal aims to fill the gaps in modeling and observing land-atmosphere interactions across scales via a novel Cross-Scale Land-Atmosphere Experiment (CSLAEX) to be implemented as part of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site near Lamont, Oklahoma. The proposed research effort aims at exploring land-atmosphere processes across multiple spatial scales and to investigate the effect of landscape heterogeneity using Distributed Temperature Sensor measurements. The novel instrumentation of the Surface Energy Balance and simultaneous observations of the atmospheric state (boundary layer, cloud, convection) available at the DOE ARM SGP site will be used to create CSLAEX. This dataset will be used to frame and evaluate new transport laws and parameterizations for the boundary layer and the land surface, which can be implemented into the Weather and Research Forecasting (WRF) model and Community Atmospheric Model (CAM). The result of this study should impact multiple fields: meteorology, climate, and hydrology.

54 ENVIRONMENTAL SCIENCES↗

Comprehensive Analysis of the Relative Dispersion of Droplet-Size Distributions and Their Relationships to Key Physical Fog Processes Under Different Aerosol Conditions and Evolutionary Stages

The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects, radiative transfer, and microphysical processes. However, previous studies have been mostly concerned with clouds, with limited studies on fog, particularly those that examine the combined influences of all key physical processes and their roles during fog evolution. As such, this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables, as well as the underlying microphysical and dynamic processes, based on field fog campaigns in polluted and clean conditions. In polluted fog, droplet concentrations are higher, leading to smaller droplets and increased dispersion. The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog, but shifts to negative in clean fog. Here, we attribute the difference to various microphysical processes like aerosol activation, condensation, collision-coalescence, and entrainment-mixing. In polluted fog, high aerosol concentrations, low supersaturations, and strong turbulence (entrainment-mixing) provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation, resulting in a positive correlation between dispersion and volume-mean radius, especially during the fog formation stage. In contrast, during the mature stage in clean fog, condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius. The collision-coalescence process is more active in the mature stage, increasing radii and leading to the negative correlation between dispersion and volume-mean radius. This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.

54 ENVIRONMENTAL SCIENCES↗

Life-Cycle Analysis of Shale Gas and Natural Gas

The technologies and practices that have enabled the recent boom in shale gas production have also brought attention to the environmental impacts of its use. Using the current state of knowledge of the recovery, processing, and distribution of shale gas and conventional natural gas, we have estimated up-to-date, life-cycle greenhouse gas emissions. In addition, we have developed distribution functions for key parameters in each pathway to examine uncertainty and identify data gaps - such as methane emissions from shale gas well completions and conventional natural gas liquid unloadings - that need to be addressed further. Our base case results show that shale gas life-cycle emissions are 6% lower than those of conventional natural gas. However, the range in values for shale and conventional gas overlap, so there is a statistical uncertainty regarding whether shale gas emissions are indeed lower than conventional gas emissions. This life-cycle analysis provides insight into the critical stages in the natural gas industry where emissions occur and where opportunities exist to reduce the greenhouse gas footprint of natural gas.

03 NATURAL GAS↗

Development of Steady-State and Dynamic Mass and Energy Constrained Neural Networks for Distributed Chemical Systems Using Noisy Transient Data

The paper presents the development of algorithms for mass and energy constrained neural network models that can exactly conserve the overall mass and energy of distributed chemical process systems, even though the noisy transient data used for optimal model training violate the same. In contrast to approximately satisfying mass and energy balance constraints of a system by soft penalization of objective function, algorithms have been developed for solving equality-constrained nonlinear optimization problems, thus providing the guarantee of exactly satisfying the system mass and energy conservation laws. For developing dynamic mass-energy constrained network models for distributed systems, hybrid series and parallel dynamic-static neural networks have been leveraged. The developed algorithms for solving both the training and forward problems are validated using both steady-state and dynamic data in the presence of various noise characteristics. The developed data-driven algorithms are flexible to exactly satisfy mass and energy balance constraints for dynamic chemical processes if the system holdup information is available. The proposed network structures and algorithms are applied to the development of data-driven lumped and distributed models of an adiabatic superheater/reheater system, a nonisothermal continuous stirred tank reactor, as well as an electrically heated plug-flow reactor system where one form of energy gets transformed to another. It has been observed that the mass-energy constrained neural networks yield a root mean squared error of <1% with respect to the system truth for the case studies evaluated in this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sensitivity study for s process nucleosynthesis in AGB stars

In this paper we present a large-scale sensitivity study of reaction rates in the main component of the s process. The aim of this study is to identify all rates, which have a global effect on the s process abundance distribution and the three most important rates for the production of each isotope. We have performed a sensitivity study on the radiative {sup 13}C-pocket and on the convective thermal pulse, sites of the s process in AGB stars. We identified 22 rates, which have the highest impact on the s-process abundances in AGB stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Automated Identification of Characteristic Droplet Size Distributions in Stratocumulus Clouds Utilizing a Data Clustering Algorithm

Abstract Droplet-level interactions in clouds are often parameterized by a modified gamma fitted to a “global” droplet size distribution. Do “local” droplet size distributions of relevance to microphysical processes look like these average distributions? This paper describes an algorithm to search and classify characteristic size distributions within a cloud. The approach combines hypothesis testing, specifically, the Kolmogorov–Smirnov (KS) test, and a widely used class of machine learning algorithms for identifying clusters of samples with similar properties: density-based spatial clustering of applications with noise (DBSCAN) is used as the specific example for illustration. The two-sample KS test does not presume any specific distribution, is parameter free, and avoids biases from binning. Importantly, the number of clusters is not an input parameter of the DBSCAN-type algorithms but is independently determined in an unsupervised fashion. As implemented, it works on an abstract space from the KS test results, and hence spatial correlation is not required for a cluster. The method is explored using data obtained from the Holographic Detector for Clouds (HOLODEC) deployed during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. The algorithm identifies evidence of the existence of clusters of nearly identical local size distributions. It is found that cloud segments have as few as one and as many as seven characteristic size distributions. To validate the algorithm’s robustness, it is tested on a synthetic dataset and successfully identifies the predefined distributions at plausible noise levels. The algorithm is general and is expected to be useful in other applications, such as remote sensing of cloud and rain properties. Significance Statement A typical cloud can have billions of drops spread over tens or hundreds of kilometers in space. Keeping track of the sizes, positions, and interactions of all of these droplets is impractical, and, as such, information about the relative abundance of large and small drops is typically quantified with a “size distribution.” Droplets in a cloud interact locally, however, so this work is motivated by the question of whether the cloud droplet size distribution is different in different parts of a cloud. A new method, based on hypothesis testing and machine learning, determines how many different size distributions are contained in a given cloud. This is important because the size distribution describes processes such as cloud droplet growth and light transmission through clouds.

54 ENVIRONMENTAL SCIENCES↗

Fickian dispersion is anomalous

The thesis put forward here is that the occurrence of Fickian dispersion in geophysical settings is a rare event and consequently should be labeled as anomalous. What people classically call anomalous is really the norm. In a Lagrangian setting, a process with mean square displacement which is proportional to time is generally labeled as Fickian dispersion. With a number of counter examples we show why this definition is fraught with difficulty. In a related discussion, we show an infinite second moment does not necessarily imply the process is super dispersive. By employing a rigorous mathematical definition of Fickian dispersion we illustrate why it is so hard to find a Fickian process. We go on to employ a number of renormalization group approaches to classify non-Fickian dispersive behavior. Scaling laws for the probability density function for a dispersive process, the distribution for the first passage times, the mean first passage time, and the finite-size Lyapunov exponent are presented for fixed points of both deterministic and stochastic renormalization group operators. The fixed points of the renormalization group operators are p-self-similar processes. A generalized renormalization group operator is introduced whose fixed points form a set of generalized self-similar processes. Finally, power-law clocks are introduced to examine multi-scaling behavior. Several examples of these ideas are presented and discussed.

58 GEOSCIENCES↗

An Integrated Modeling Framework for Sediment Dynamics During Urban Flooding: Application to Hurricane Harvey in Houston

Floodwater can mobilize and redistribute large volumes of sediment from upland to downstream urban areas, threatening infrastructure, water quality, and ecosystem health. However, existing modeling approaches often fail to capture sediment dynamics in urban floodplains due to the lack of integration between upland hydrological processes and riverine sediment transport. This study presents the first integrated modeling framework that couples the Energy Exascale Earth System Model (E3SM) land component, which simulates runoff and hillslope erosion, with TELEMAC-GAIA, a two-dimensional hydrodynamic and sediment transport model. This framework enables the fully distributed, process-based simulation of high-resolution (as fine as 30 m) sediment dynamics from hillslopes to floodplains. Applied to a highly urbanized watershed in Houston during Hurricane Harvey, this framework reproduced observed water levels at 16 USGS gauges (median R 2 = 0.83 and KGE = 0.78), key sediment dynamics such as sediment transport and deposition processes, and reproduced spatial deposition patterns consistent with LiDAR-derived data. Based on the simulation, we estimate 8.0 million m 3 of event-scale sediment deposition, including 5.7 million m 3 trapped in the flood-control reservoirs and 2.3 million m 3 deposited along major channels and floodplains. Using a representative unit removal cost, this corresponds to an estimated dredging cost of $581 million for total deposition. These results provide a first-order, physically based quantification of Harvey-scale sediment impacts. This study provides a valuable tool for the holistic analysis of sediment dynamics triggered by extreme urban flooding, supporting flood-resilience planning. More broadly, it highlights the importance of integrating physically based hydrological processes for urban flooding and sediment research.

Hurricane Harvey↗

Using spatial statistical methods to determine an effective minimum detectable activity - 15681

Instrument minimum detectable activity (MDA) is generally established by collecting multiple measurements over time of a single representative background location to estimate a probability distribution of instrument readings. A reading that is considered to be greater than would be expected from the background probability distribution (i.e., a low-probability event) is deemed to be sufficiently unlikely that it must be attributable to added radioactivity and is therefore used as the instrument MDA. An effective MDA can be determined from spatially distributed data that are much lower than the instrument MDA. This has been accomplished using a large number of spatially distributed data points (from a radiation survey) where patterns of elevated survey readings can be distinguished from background at levels. Given the variation of the instrument response and the relatively low regulatory action levels, it is vital to establish MDA thresholds that are well below corrective action levels. Processing of radiological survey data with the use of histogram binning and geo-statistics in enabling pattern recognition can be used to establish effective field MDAs that are much lower than instrument MDAs. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Modification of Particle Distributions by MHD Instabilities II

The modification of particle distributions by low amplitude magnetohydrodynamic modes is an important topic for magnetically confined plasmas. Low amplitude modes are known to be capable of producing significant modification of injected neutral beam profiles, and the same can be expected in burning plasmas for the alpha particle distributions. Flattening of a distribution in an island due to phase mixing and portions of phase space becoming stochastic lead to modification of the particle distribution, a process extremely rapid in the time scale of an experiment but still very long compared to the time scale of guiding center simulations. Large amplitude modes can cause profile avalanche and particle loss. Thus it is very valuable to be able to predict the temporal evolution of a particle distribution produced by a given spectrum of magnetohydrodynamic modes. In this paper we further develop and investigate the use of a new method of determining domains of phase space in which good KAM surfaces do not exist and use this method to examine a well documented case of profile modification by instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Co-Design Study Of Fusion Whole Device Modeling Using Code Coupling

Complex workflows consisting of multiple simulation and analysis codes running concurrently through in-memory coupling is becoming popular due to inherent advantages in online management of large-scale data, resilience, and the code development process. However, orchestrating such a multi-application workflow to efficiently utilize resources on a heterogeneous architecture is challenging. In this paper, we present our results with running the Fusion Whole Device Modeling benchmark workflow on Summit, a pre-exascale supercomputer at Oak Ridge National Laboratory. We explore various resource distribution and process placement mechanisms, including sharing compute nodes between processes from separate applications. We show that fine-grained process placement can have a significant impact towards efficient utilization of the compute power of a node on Summit, and conclude that sophisticated tools for performing co-design studies of multi-application workflows can play an important role towards efficient orchestration of such workflows.

Choi, Jong Youl↗

State Energy Justice Roundtable Series: Energy Justice Metrics

The National Association of Regulatory Utility Commissioners (NARUC), National Association of State Energy Officials (NASEO), and National Governors Association (NGA) hosted a State Energy Justice Roundtable (Roundtable) in April 2022. Participants included federal and state decision-makers, members of community-based organizations, and subject-matter experts. The Roundtable members explored current state efforts to articulate and incorporate energy justice concerns into energy-related decision-making. Participants established connections with one another to better understand the current landscape of existing resources, learn about emerging efforts, and identify ongoing support opportunities for advancing energy justice.This paper is one of five authored by the host organizations on topics that were the focus of the Roundtable. Each paper summarizes key themes, emerging efforts, and group takeaways that were discussed at the Roundtable and should assist state members in developing and meeting their own state goals around energy justice. The papers all include the same discussions of background, introduction, and reading list so they can be read separately. Each paper is written from the perspective of one association and includes options for its members to take actions that could support more equitable state energy policies and programs. The five papers cover: (1) Participation in decision making (NARUC), (2) Customer affordability and arrearages (NARUC), (3) Energy justice metrics (NARUC), (4) Equity in clean energy research and development (NASEO), and (5) Equitable distributed energy resource (DER) access (NGA). The resources and recommendations listed in these papers are not meant to be exhaustive, as this field of study continues to evolve. Although this brief is focused on electricity, energy justice considerations extend to all energy needs and services, including the impact of energy extraction, processing, and distribution functions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

State Energy Justice Roundtable Series: Customer Affordability and Arrearages

The National Association of Regulatory Utility Commissioners (NARUC), National Association of State Energy Officials (NASEO), and National Governors Association (NGA) hosted a State Energy Justice Roundtable (Roundtable) in April 2022. Participants included federal and state decision-makers, members of community-based organizations, and subject-matter experts. The Roundtable members explored current state efforts to articulate and incorporate energy justice concerns into energy-related decision-making. Participants established connections with one another to better understand the current landscape of existing resources, learn about emerging efforts, and identify ongoing support opportunities for advancing energy justice. This paper is one of five authored by the host organizations on topics that were the focus of the Roundtable. Each paper summarizes key themes, emerging efforts, and group takeaways that were discussed at the Roundtable and should assist state members in developing and meeting their own state goals around energy justice. The papers all include the same discussions of background, introduction, and reading list so they can be read separately. Each paper is written from the perspective of one association and includes options for its members to take actions that could support more equitable state energy policies and programs. The five papers cover: (1) Participation in decision making (NARUC) (2) Customer affordability and arrearages (NARUC) (3) Energy justice metrics (NARUC) (4) Equity in clean energy research and development (NASEO) (5) Equitable distributed energy resource (DER) access (NGA). The resources and recommendations listed in these papers are not meant to be exhaustive, as this field of study continues to evolve. Although this brief is focused on electricity, energy justice considerations extend to all energy needs and services, including the impact of energy extraction, processing, and distribution functions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

State Energy Justice Roundtable Series: Participation in Decision Making

The National Association of Regulatory Utility Commissioners (NARUC), National Association of State Energy Officials (NASEO), and National Governors Association (NGA) hosted a State Energy Justice Roundtable (Roundtable) in April 2022. Participants included federal and state decision-makers, members of community-based organizations, and subject-matter experts. The Roundtable members explored current state efforts to articulate and incorporate energy justice concerns into energy-related decision-making. Participants established connections with one another to better understand the current landscape of existing resources, learn about emerging efforts, and identify ongoing support opportunities for advancing energy justice. This paper is one of five authored by the host organizations on topics that were the focus of the Roundtable. Each paper summarizes key themes, emerging efforts, and group takeaways that were discussed at the Roundtable and should assist state members in developing and meeting their own state goals around energy justice. The papers all include the same discussions of background, introduction, and reading list so they can be read separately. Each paper is written from the perspective of one association and includes options for its members to take actions that could support more equitable state energy policies and programs. The five papers cover: • Participation in decision making (NARUC) • Customer affordability and arrearages (NARUC) • Energy justice metrics (NARUC) • Equity in clean energy research and development (NASEO) • Equitable distributed energy resource (DER) access (NGA). The resources and recommendations listed in these papers are not meant to be exhaustive, as this field of study continues to evolve. Although this brief is focused on electricity, energy justice considerations extend to all energy needs and services, including the impact of energy extraction, processing, and distribution functions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Thermodynamics of the Inner Heliosheath

We derive annual sky maps of the proton temperature in the inner heliosheath (IHS), and track their temporal evolution over the years 2009–2016 of Interstellar Boundary Explorer observations. Other associated thermodynamic parameters also determined are the density, kappa (the parameter that characterizes kappa distributions), temperature rate, polytropic index, and entropy. We exploit the theory of kappa distributions and their connection with polytropes, to (i) express a new polytropic quantity Π that remains invariant along streamlines where temperature and density may vary, (ii) parameterize the proton flux in terms of the Π invariant and kappa, and (iii) derive the temperature and density, respectively, from the slope and intercept of the linear relationship between kappa and logarithm of Π. We find the following thermodynamic characteristics: (1) temperature sky maps and histograms shifted to their lowest values in 2012 and their highest in 2015; (2) temperature negatively correlated with density, reflecting the subisothermal polytropic behavior; (3) temperature positively correlated with kappa, revealing characteristics of the mechanism responsible for generating kappa distributions; (4) processes in IHS are subisothermal tending toward isobaric, consistent with previously published results; (5) linear relationship between kappa and polytropic indices, revealing characteristics of the particle potential energy; and (6) entropy positively correlated with polytropic index, aligned with the underlying theory that entropy increases toward the isothermal state where the kappa distribution reduces to the Maxwell–Boltzmann description.

79 ASTRONOMY AND ASTROPHYSICS↗

Riverine bacterioplankton and phytoplankton assembly along an environmental gradient induced by urbanization

In the Anthropocene, human activities are intensifying stresses on biological communities across ecosystems. Knowledge on how environmental changes influence microbial community dynamics is crucial but currently limited. Here we unraveled ecological processes generating distribution patterns of bacterioplankton and phytoplankton communities in a river draining an urbanizing watershed in southern China. In this ecosystem, longitudinal environmental heterogeneity and directional flow potentially have counteracting effects on planktonic community assembly. Using simultaneously multiple approaches, we showed that the observed compositional patterns result from an interplay of stochastic and deterministic processes, indicating that dispersal via fluvial connectivity could not override local selective pressures. Successional shifts in the relative importance of the above processes were associated with trends in climatic factors. High diversity was observed at the intermediate levels of ecological processes alongside intense inter-species interactions maintained by a few keystone taxa. Altogether, interactions between climatic conditions, landscape and hydrology control plankton community dynamics.

54 ENVIRONMENTAL SCIENCES↗

Validation of New Process Models for Large Injection-Molded Long-Fiber Thermoplastic Composite Structures

This report describes the work conducted under the CRADA Nr. PNNL/304 between Battelle PNNL and Autodesk whose objective is to validate the new process models developed under the previous CRADA for large injection-molded LFT composite structures. To this end, the ARD-RSC and fiber length attrition models implemented in the 2013 research version of Moldflow was used to simulate the injection molding of 600-mm x 600-mm x 3-mm plaques from 40% glass/polypropylene (Dow Chemical DLGF9411.00) and 40% glass/polyamide 6,6 (DuPont Zytel 75LG40HSL BK031) materials. The injection molding was performed by Injection Technologies, Inc. at Windsor, Ontario (under a subcontract by Oak Ridge National Laboratory, ORNL) using the mold offered by the Automotive Composite Consortium (ACC). Two fill speeds under the same back pressure were used to produce plaques under slow-fill and fast-fill conditions. Also, two gating options were used to achieve the following desired flow patterns: flows in edge-gated plaques and in center-gated plaques. After molding, ORNL performed measurements of fiber orientation and length distributions for process model validations. The structure of this report is as follows. After the Introduction (Section 1), Section 2 provides a summary of the ARD-RSC and fiber length attrition models. A summary of model implementations in the latest research version of Moldflow is given in Section 3. Section 4 provides the key processing conditions and parameters for molding of the ACC plaques. The validations of the ARD-RSC and fiber length attrition models are presented and discussed in Section 5. The conclusions will be drawn in Section 6.

36 MATERIALS SCIENCE↗

An Informatics Approach to Demand Response Optimization in Smart Grids

Power utilities are increasingly rolling out “smart” grids with the ability to track consumer power usage in near real-time using smart meters that enable bidirectional communication. However, the true value of smart grids is unlocked only when the veritable explosion of data that will become available is ingested, processed, analyzed and translated into meaningful decisions. These include the ability to forecast electricity demand, respond to peak load events, and improve sustainable use of energy by consumers, and are made possible by energy informatics. Information and software system techniques for a smarter power grid include pattern mining and machine learning over complex events and integrated semantic information, distributed stream processing for low latency response,Cloud platforms for scalable operations and privacy policies to mitigate information leakage in an information rich environment. Such an informatics approach is being used in the DoE sponsored Los Angeles Smart Grid Demonstration Project, and the resulting software architecture will lead to an agile and adaptive Los Angeles Smart Grid.

Simmhan, Yogesh↗