Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data flow”

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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cyber-Power Co-Simulation for End-to-End Synchrophasor Network Analysis and Applications

The resiliency, reliability and security of the next generation cyber-power smart grid depend upon efficiently leveraging advanced communication and computing technologies. Also, developing real-time data-driven applications is critical to enable wide-area monitoring and control of the cyber-power grid given high-resolution data from Phasor Measurement Units (PMUs). North American Synchrophasor Initiative Network (NASPlnet) provides guidance for PMU data exchanges. With the advancement in networking and grid operation, it is necessary to evaluate the performance of different data flow architectures suggested by NASPInet and analyze the impact on applications. Therefore, we need a cyber-power co-simulation framework that supports very large-scale co-simulation capable of running in parallel, high-performance computing platforms and capturing real-life network behavior. This work presents an end-to-end automated and user-driven cyber-power co-simulation using NS3 to model communication networks, GridPACK to model the power grid, and HELICS as a co-simulation engine. Comparative analysis of latency in synchrophasor networks and a performance evaluation of a power system stabilizer application utilizing PMU data in an IEEE 39 bus test system is presented using this cosimulation testbed.

Mustafa, Hussain M.↗
DOE OSTI2022

Digitalization of an experimental electrochemical reactor via the smart manufacturing innovation platform

The exponential increase in data produced over the last two decades has revolutionized the way we collect, store, process, analyze, model, and interpret information to improve profitability. Manufacturing is no exception. How- ever, Smart Manufacturing, the digital practice, organization, workforce, and infrastructure transformation for collection and deployment of data and models at scale and at all levels of manufacturing, is a complex, costly, and labor-intensive journey that is still seeing slow adoption. The Clean Energy Smart Manufacturing Innovation Institute (CESMII), a national Manufacturing USA public-private partnership sponsored by the Department of Energy, is addressing this scaled use of data and modeling in manufacturing. CESMII has focused on how to col- lect and use operating data for numerous applications that improve productivity, precision, and performance of manufacturing operations from factory floor to supply chain using process simulation, predictive analytics, mon- itoring and control, and real-time optimization. Because contextualized data are key, CESMII has developed the Smart Manufacturing Innovation Platform (SMIP) to lower the barriers to the data that are needed to accelerate data-based model building, improve data visualization, and more quickly gain insights. Reusable, standards-based ways of doing data collection, ingestion, and contextualization are particularly important for scaling access and use of data. The SMIP uses a standards-based definition and construct for reusable information models called an SM Profile. When an SM Profile is used in conjunction with the SMIP, the SMIP ensures the availability of contextualized, operational data for model building. The present work demonstrates Smart Manufacturing and the application of the SMIP for building several data-centered models for the operation and control of an ex- perimental electrochemical reactor that reduces carbon dioxide (CO 2 ) gas to valuable liquid and gas chemicals, such as alcohols, olefins, and syngas. We describe how the SMIP plays a central role in more effective model building and we demonstrate how the electochemical reactor can be controlled and optimized for the desired products. Use of the SMIP involves the transmission of real-time sensor measurements to a cloud resource so that the operating data are available to all model building experts. The data collection and transmission process is fully automated to greatly reduce the need for manual manipulation of the data. Data-driven machine learning models are used for advanced real-time state estimation, real-time optimization, and model-based feedback control for the reactor. The application models are implemented as a system to monitor the data flow and control the electrochemical reactor with a single visualization interface. SM Profiles are used to demonstrate reusability of the information models for the reactor and the instrumentation. The application packages, algorithms, and user interfaces developed are cast as Docker images in a library to facilitate reusability of the application models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Hydra: computer vision for data quality monitoring

Hydra, initially developed for Hall-D in 2019, is a system that utilizes computer vision to perform near real time data quality monitoring. Since then, it has been deployed across all experimental halls at Jefferson Lab, with the CLAS12 collaboration in Hall-B being the first outside of GlueX to fully utilize Hydra. The system comprises back end processes that manage the models, their inferences, and the data flow. Finally, the front-end components, accessible via web pages, allow detector experts and shift crews to view and interact with the system.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Life-cycle Analysis of Bioproducts and Their Conventional Counterparts in GREET

To further expand upon the literature in this field and to develop a platform for bioproduct LCA, we developed LCA results for ten bioproducts produced either from algal glycerol or from corn stover-derived sugars. We used Argonne National Laboratory’s Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREETTM) model as the platform for this study. The data and calculations reported herein are available to GREET users in a bioproducts module included in the fall 2015 GREET release. This report documents our approach to this analysis and the results. In Chapter 2, we review the process we underwent to select the bioproducts for analysis based on market and technology readiness criteria. In Chapter 3, we review key parameters for production of the two feedstocks we considered: corn stover and algae. Given the lack of publicly available information about the production of bioproducts, which is caused in large part by the emerging nature of the industry, we developed Aspen Plus® simulations of the processes that could be used to produce each bioproduct. From these simulations, we extracted the energy and material flows of these processes, which were important inputs to the GREET bioproducts module. Chapter 4 provides the details of these Aspen Plus simulations. It is important to compare the LCA results for bioproducts to those for their petroleum counterparts. We therefore also developed material and energy flow data for conventional products based mostly on the literature. These data are described in Chapter 5 and are also included in the GREET bioproducts module. In Chapter 6, we present results from this analysis and examine areas for refinement and future research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

MERIDIONAL FLOW IN THE SOLAR CONVECTION ZONE. II. HELIOSEISMIC INVERSIONS OF GONG DATA

Meridional flow is thought to play a very important role in the dynamics of the solar convection zone; however, because of its relatively small amplitude, precisely measuring it poses a significant challenge. Here we present a complete time–distance helioseismic analysis of about 2 years of ground-based Global Oscillation Network Group (GONG) Doppler data to retrieve the meridional circulation profile for modest latitudes in an attempt to corroborate results from other studies. We use an empirical correction to the travel times due to an unknown center-to-limb systematic effect. The helioseismic inversion procedure is first tested and reasonably validated on artificial data from a large-scale numerical simulation followed by a test to broadly recover the solar differential rotation found from global seismology. From GONG data, we measure poleward photospheric flows at all latitudes with properties that are comparable with earlier studies and a shallow equatorward flow about 65 Mm beneath the surface, in agreement with recent findings from Helioseismic and Magnetic Imager (HMI) data. No strong evidence of multiple circulation cells in depth or latitude is found, yet the whole phase space has not yet been explored. Tests of mass flux conservation are then carried out on the inferred GONG and HMI flows and compared to a fiducial numerical baseline from models, and we find that the continuity equation is poorly satisfied. While the two disparate data sets do give similar results for about the outer 15% of the interior radius, the total inverted circulation pattern appears to be unphysical in terms of mass conservation when interpreted over modest time scales. We can likely attribute this to both the influence of realization noise and subtle effects in the data and measurement procedure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

(U) Ristra Next Generation Code Report

LANL’s Weapons Physics management (ADX) and ASC program office have defined a strategy for exascale-class application codes that follows two supportive, and mutually risk-mitigating paths: evolution for established codes (with a strong pedigree within the user community) based upon existing programming paradigms (MPI+X); and Ristra (formerly known as NGC), a high-risk/high-reward push for a next-generation multi-physics, multi-scale simulation toolkit based on emerging advanced programming systems (with an initial focus on data-flow task-based models exemplified by Legion [5]). Development along these paths is supported by the ATDM, IC, and CSSE elements of the ASC program, with the resulting codes forming a common ecosystem, and with algorithm and code exchange between them anticipated. Furthermore, solution of some of the more challenging problems of the future will require a federation of codes working together, using established-pedigree codes in partnership with new capabilities as they come on line. The role of Ristra as the high-risk/high-reward path for LANL’s codes is fully consistent with its role in the Advanced Technology Development and Mitigation (ATDM) sub-program of ASC (see Appendix C), in particular its emphasis on evolving ASC capabilities through novel programming models and data management technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Data-Driven Algorithm for Enabling Delay Tolerance in Resilient Microgrid Controls Using Dynamic Mode Decomposition

The increased implementation of smart grid technologies in the power distribution grid presents unique opportunities that enable resiliency, but also brings challenges motivating needs for novel solutions and mitigation techniques. The bi-directional power and data flow allow for the grid to operate with increased resiliency, which is the ability to avoid discontinuity of service to end-use loads during extreme events. However, in applications where control of the distribution grid or microgrid relies on communication networks, the degradation of communication systems in the form of loss or high latency can cause maloperation and result in loss of end-use loads. Here this paper presents a novel framework to enable delay tolerance of centralized microgrid control schemes to mitigate communication system latency impacts and guarantee successful control action. We demonstrate the delay tolerance on a control scheme that operates a battery energy storage system (BESS) to offset the sudden loss of generation and maintain system frequency. During periods of severely degraded communication system performance, the proposed delay-tolerant algorithm compensates for the latency by utilizing a data-driven model generated at the device level using dynamic mode decomposition (DMD) to determine the performance of the communications. The DMD technique predicts the system’s frequency using device-level terminal measurements and provides updated control signals. The HELICS cosimulation platform evaluates the cyber-physical interaction of the power system model in GridLAB-D, the centralized control agent in Python, and the discrete network model in NS-3. The framework is tested and validated on the IEEE-123 node system modified to represent a networked remote microgrid model, and the results show an improvement in the dynamic performance

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

A Comprehensive View of Global Potential for Hydro-generated Electricity

In this study, we assess global hydropower potential using runoff and stream flow data, along with turbine technology performance, cost assumptions, and environmental considerations. The results provide the first comprehensive quantification of global hydropower potential including gross, technical, economic, and exploitable estimates. Total global potential of gross, technical, economic, and exploitable hydropower are estimated to be approximately 128, 39, 32, and 27 petawatt hours per year, respectively. The economic and exploitable potential of hydropower are calculated at less than 9 cents/kWh. We find that hydropower has the potential to supply a significant portion of the world energy needs, although this potential varies substantially by region. Globally, hydropower can potentially supply about 1.5 times the total electricity demand in 2005. Estimated hydropower resources in a number of countries are sufficient to accommodate their demand for electricity in 2005, e.g., Brazil (5.6 times), Russia (4.6 times), and Canada (3.5 times). A sensitivity analysis indicates that hydropower estimates are not highly sensitive to five key parameters: design flow (varying by -2% to +1% at less than 9 cents/kWh), cost and financing options (by -7% to +6%), turbine efficiency (by -10% to +10%), stream flow (by -10% to +10%), and fixed charge rate (by -6% to 5%). This sensitivity analysis emphasizes the reliable role of hydropower for future energy systems, when compared to other renewable energy resources with larger uncertainty in their future potentials.

Zhou, Yuyu↗
DOE OSTI2015

A Scalable Monitoring for the CMS Filter Farm Based on Elasticsearch

A flexible monitoring system has been designed for the CMS File-based Filter Farm making use of modern data mining and analytics components. All the metadata and monitoring information concerning data flow and execution of the HLT are generated locally in the form of small documents using the JSON encoding. These documents are indexed into a hierarchy of elasticsearch (es) clusters along with process and system log information. Elasticsearch is a search server based on Apache Lucene. It provides a distributed, multitenant-capable search and aggregation engine. Since es is schema-free, any new information can be added seamlessly and the unstructured information can be queried in non-predetermined ways. The leaf es clusters consist of the very same nodes that form the Filter Farm thus providing natural horizontal scaling. A separate central” es cluster is used to collect and index aggregated information. The fine-grained information, all the way to individual processes, remains available in the leaf clusters. The central es cluster provides quasi-real-time high-level monitoring information to any kind of client. Historical data can be retrieved to analyse past problems or correlate them with external information. We discuss the design and performance of this system in the context of the CMS DAQ commissioning for LHC Run 2.

Andre, J. M.↗
DOE OSTI2018

An Overview of the EGS Collab Project: Field Validation of Coupled Process Modeling of Fracturing and Fluid Flow at the Sanford Underground Research Facility, Lead, SD

Enhanced Geothermal Systems (EGS) development will require an ability to accurately predict the flow rates and temperatures of the production wells. While simple in concept, complex heterogeneous fracture pathways can lead to channeling, short-circuiting, and premature thermal breakthrough complicating EGS. The EGS Collab project will establish a suite of intermediate-scale (~10-20 m) field test beds coupled with stimulation and interwell flow tests to provide a basis to better understand the fracture geometries and processes that control heat transfer between rock and stimulated fractures. These experiments will provide a means of testing tools, codes, and concepts that could later be employed under geothermal reservoir conditions at FORGE and in EGS. We will perform well-controlled, in situ experiments focused on rock fracture behavior and permeability enhancement. Pre- and post-test modeling of each test will allow for model prediction and validation. Comprehensive instrumentation will be used to collect high-quality, high-resolution geophysical and fracture characterization and fluid flow data. ,These data will be analyzed and compared with models and field observations to further elucidate the basic relationships between stress, induced seismicity, and permeability enhancement. To the maximum extent achievable, we will observe and quantify other key governing parameters that impact permeability, and attempt to understand how these parameters might change throughout the development and operation of an EGS project with the goal of enabling commercial viability of EGS. The Sanford Underground Research Facility (SURF) in South Dakota was selected as the EGS Collab project experimental site based on the evaluation of information from several sites. Our team has designed and constructed the first field experiment planned for this project, which is supported by the US Department of Energy’s Geothermal Technologies Office.

EGS, FORGE, field fracture stimulation and flow ex↗
DOE OSTI2021

Blockchain-Based Smart Contracts Use for Photovoltaic Energy Trade Transactions

In recent decades, interest in renewable energy via solar energy has increased, especially in California and Nevada. In a region that can produce enough solar power for self-use, prosumers must use or sell surplus energy. Solar energy self-consumption is essential in modern energy transactions in the grid. This paper proposes an approach towards grid services that includes photovoltaic hardware to store the excess energy in battery storage. Such energy can then be sold to power companies while the transaction is handled using blockchain. Software, security architecture and data flow requirements based on the Ethereum Blockchain are included. Furthermore, this solution protects the private information of seller and buyer and secures transactions.

14 SOLAR ENERGY↗
DOE OSTI2015

Jagged Tiling for Intra-tile Parallelism and Fine-Grain Multithreading

In this paper, we have developed a novel methodology that takes into consideration multithreaded many-core designs to better utilize memory/processing resources and improve memory residence on tileable applications. It takes advantage of polyhedral analysis and transformation in the form of PLUTO, combined with a highly optimized finegrain tile runtime to exploit parallelism at all levels. The main contributions of this paper include the introduction of multi-hierarchical tiling techniques that increases intra tile parallelism; and a data-flow inspired runtime library that allows the expression of parallel tiles with an efficient synchronization registry. Our current implementation shows performance improvements on an Intel Xeon Phi board up to 32.25% against instances produced by state-of-the-art compiler frameworks for selected stencil applications.

compiler↗
DOE OSTI2019

Allometric relationships between primary size measures and sapwood area for six common tree species in snow-dependent ecosystems in the Southwest United States

High-elevation, snow-dependent, semiarid ecosystems across southwestern United States are expected to be vulnerable to climate change, including drought and fire, with implications for various aspects of the water cycle. To that end, much less is known about the dynamics of transpiration, an important component of the water cycle across this region. At the individual-tree scale, transpiration is estimated by scaling mean sap flux density by the hydroactive sapwood area (SA). SA also remains a key factor in effectively scaling individual tree water-use to stand level. SA across large spatial scales is normally established by relating SA of a few trees to primary size measures, e.g., diameter at breast height (DBH), tree height ( H ), or canopy diameter (CD). Considering the importance of SA in scaling transpiration, the primary objective of this study was therefore to establish six species-specific (aspen, maple, white fir, ponderosa pine, Douglas fir, Englemann spruce) allometric relationships between SA and three primary size measures (DBH, CD, or H ) across two high-elevation, snow-dependent, semiarid ecosystems in New Mexico and Arizona. Based on multiple statistical criteria (coefficient of determination, index of agreement, Nash–Sutcliffe efficiency) and ease of measurement in the forest, we identified DBH as the primary independent variable for estimating SA across all sites. Based on group regression analysis, we found allometric relationships to be significantly ( p < 0.05) different for the same species (ponderosa pine, Douglas-fir) across different sites. Overall, our allometric relationships provide a valuable database for estimating transpiration at different spatial scales from sap flow data in some of our most vulnerable ecosystems.

Forestry↗
DOE OSTI2016

Interflow dynamics on a low relief forested hillslope: Lots of fill, little spill

In this paper, we evaluated the occurrence of perching and interflow over and within a sandy clay loam argillic horizon within first-order, low-relief, forested catchments at the Savannah River Site (SRS) in the Upper Coastal Plain of South Carolina. We measured soil hydraulic properties, depths to the argillic layer, soil moisture, shallow groundwater behavior, interflow interception trench flows, and streamflow over a 4-year period to explore the nature and variability of soil hydraulic characteristics, the argillic “topography”, and their influence on interflow generation. Perching occurred frequently within and above the restricting argillic horizons during our monitoring period, but interflow was infrequent due to microtopographic relief and associated depression storage on the argillic layer surface. High percolation rates through the argillic horizon, particularly through soil anomalies, also reduced the importance of interflow. Interflow generation was highly variable across eleven segments of a 121 m interception trench. Hillslopes were largely disconnected from stream behavior during storms. Hillslope processes were consistent with the fill-and-spill hypothesis and featured a sequence of distinct thresholds: vertical wetting front propagation to the argillic layer; saturation of the argillic followed by local perching; filling of argillic layer depressions; and finally connectivity of depressions leading to interflow generation. Lastly, analysis of trench flow data indicated a cumulative rainfall threshold of 60 mm to generate interflow, a value at the high end of the range of thresholds reported elsewhere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Sustainable sanitary landfills for neglected small cities in developing countries: The semi-mechanized trench method from Villanueva, Honduras

Highlights: Black-Right-Pointing-Pointer Open dumping is the most common form of waste disposal in neglected small cities. Black-Right-Pointing-Pointer Semi-mechanized landfills can be a sustainable option for small cities. Black-Right-Pointing-Pointer We present the theory of design and operation of semi-mechanized landfills. Black-Right-Pointing-Pointer Villanueva, Honduras has operated its semi-mechanized landfill for 15 years. Black-Right-Pointing-Pointer The cost of operation is US$4.60/ton with a land requirement of 0.2m{sup 2}/person-year. - Abstract: Open dumping is the most common practice for the disposal of urban solid wastes in the least developed regions of Africa, Asia and Latin America. Sanitary landfill design and operation has traditionally focused on large cities, but cities with fewer than 50,000 in population can comprise from 6% to 45% of a given country's total population. These thousands of small cities cannot afford to operate a sanitary landfill in the way it is proposed for large cities, where heavy equipment is used to spread and compact the waste in daily cells, and then to excavate, transport and apply daily cover, and leachate is managed with collection and treatment systems. This paper presents an alternative approach for small cities, known as the semi-mechanized trench method, which was developed in Villanueva, Honduras. In the semi-mechanized trench method a hydraulic excavator is used for 1-3 days to dig a trench that will last at least a month before it is filled with waste. Trucks can easily unload their wastes into the trench, and the wastes compact naturally due to semi-aerobic biodegradation, after which the trenches are refilled and covered. The exposed surface area is minimal since only the top surface of the wastes is exposed, the remainder being covered by the sides and bottom of the trench. The surplus material from trench excavation can be valorized for use as engineering fill onsite or off. The landfill in Villanueva has operated for 15 years, using a total land area of approximately 11 ha for a population that grew from 23,000 to 48,000, with a land requirement of 0.2 m{sup 2}/person year, a cover to waste ratio of 0.2, and an estimated soil surplus of 298,000 m{sup 3} that is valorized and used onsite. The landfill has been operated solely by the municipality with an operational cost in 2010 estimated at US$4.60 per ton. A modified water balance analysis at Villanueva shows negligible leachate generation from covered trenches and 700 m{sup 3}/yr (60 m{sup 3}/ha yr) from the two open trenches required for daily operation. If the site were an open dump, however, leachate generation is estimated to be 3900 m{sup 3}/ha yr and contaminated runoff 5000 m{sup 3}/ha yr. A simple model used to estimate dilution of generated leachate based on groundwater flow data and aquifer stratigraphy suggests that the leachate will be diluted by a factor of 0.01 in the aquifer. Leachate contaminants will not accumulate because the aquifer discharges to the Ulua River 2 km south of the landfill. While not suitable for all sites, the Villanueva method nevertheless serves as an excellent example of how a small city landfill with natural compaction of waste and attenuation of leachate can be sustainably operated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Optimal Pathways from Alternative Carbon Feedstocks to Organic Commodity Chemicals

The use of biogenic and waste feedstocks is a promising strategy to improve the chemical sector's supply chain resiliency and carbon intensity. To help inform research efforts that transform these feedstocks into industrial chemicals, we used a systematic analysis framework to consistently evaluate the economics and environmental impacts of >200 alternative production pathways for 51 organic commodity chemicals in the United States under an optimistic future scenario that reflects the potential upper bounds of process scalability, energy availability, and carbon uptake. Lower-impact and lower-cost alternative pathways were identified for all but three chemicals, with 75% using thermochemical routes and half leveraging existing manufacturing infrastructure. Scenario analysis shows that the ranking of these pathways for half of the assessed chemicals is particularly sensitive to carbon uptake assumptions and criteria prioritization (i.e., cost only, environmental impact only, or both), with changes in electricity grid mix, hydrogen source, and underlying mass and energy flow data proving less influential. Implementing alternative pathways for just 11 chemicals could support a transition to net-zero greenhouse gas emissions from chemical production by 2050, with 11% lower cost than business as usual, similar water requirements, quadrupled electricity demand, and the use of most available woody biomass. These findings provide an exploratory guide toward a future chemical industry that harnesses alternative feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2012

Calibration of a distributed flood forecasting model with input uncertainty using a Bayesian framework

In the process of calibrating distributed hydrological models, accounting for input uncertainty is important, yet challenging. In this study, we develop a Bayesian model to estimate parameters associated with a geomorphology‐based hydrological model (GBHM). The GBHM model uses geomorphic characteristics to simplify model structure and physically based methods to represent hydrological processes. We divide the observed discharge into low‐ and high‐flow data, and use the first‐order autoregressive model to describe their temporal dependence. We consider relative errors in rainfall as spatially distributed variables and estimate them jointly with the GBHM parameters. The joint posterior probability distribution is explored using Markov chain Monte Carlo methods, which include Metropolis‐Hastings, delay rejection adaptive Metropolis, and Gibbs sampling methods. We evaluate the Bayesian model using both synthetic and field data sets. The synthetic case study demonstrates that the developed method generally is effective in calibrating GBHM parameters and in estimating their associated uncertainty. The calibration ignoring input errors has lower accuracy and lower reliability compared to the calibration that includes estimation of the input errors, especially under model structure uncertainty. The field case study shows that calibration of GBHM parameters under complex field conditions remains a challenge. Although jointly estimating input errors and GBHM parameters improves the continuous ranked probability score and the consistency of the predictive distribution with the observed data, the improvement is incremental. To better calibrate parameters in a distributed model, such as GBHM here, we need to develop a more complex model and incorporate much more information.

54 ENVIRONMENTAL SCIENCES↗