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At least 649 records · Page 36

Roll-Yaw control at high angle of attack by forebody tangential blowing

The feasibility of using forebody tangential blowing to control the roll-yaw motion of a wind tunnel model is experimentally demonstrated. An unsteady model of the aerodynamics is developed based on the fundamental physics of the flow. Data from dynamic experiments is used to validate the aerodynamic model. A unique apparatus is designed and built that allows the wind tunnel model two degrees of freedom, roll and yaw. Dynamic experiments conducted at 45 degrees angle of attack reveal the system to be unstable. The natural motion is divergent. The aerodynamic model is incorporated into the equations of motion of the system and used for the design of closed loop control laws that make the system stable. These laws are proven through dynamic experiments in the wind tunnel using blowing as the only actuator. It is shown that asymmetric blowing is a highly non-linear effector that can be linearized by superimposing symmetric blowing. The effects of forebody tangential blowing and roll and yaw angles on the flow structure are determined through flow visualization experiments. The transient response of roll and yaw moments to a step input blowing are determined. Differences on the roll and yaw moment dependence on blowing are explained based on the physics of the phenomena.

Pedreiro, N.↗

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↗

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↗

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.↗

Swirl flow turbulence modeling

Confined turbulent swirling flow data obtained from a single hot-wire using a six-orientation technique are analyzed numerically. The effects of swirl strength and the presence of a strong contraction nozzle further downstream on deduced parameters is also presented and discussed for the case of chamber-to-inlet diameter ratio D/d = 2. Three swirl strengths are considered with inlet swirl vane angles of 0, 45 and 70 deg. A strong contraction nozzle with an area ratio of 4 is located two chamber-diameters downstream of the inlet to the flowfield. It is found that both the swirl strength and the contraction have strong effects on the turbulence parameters. Generally, the most dramatic effect of increase of swirl strength is the considerable increase in values of all the parameters considered, (rx-viscosity, kinetic energy of turbulence, length scales, and degree of nonisotropy). The presence of a strong contraction nozzle tends to increase the turbulence parameter values in regions of acceleration and to reduce them in deceleration regions. Based on similarity of viscosity and length scale profiles, a C sub mu formulation is deduced which is shown to improve the predictive capability of the standard k-epsilon turbulence model in swirling recirculating flows.

Abujelala, M. T.↗

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↗

Determining Sizes of Particles in a Flow from DPIV Data

A proposed method of measuring the size of particles entrained in a flow of a liquid or gas would involve utilization of data from digital particle-image velocimetry (DPIV) of the flow. That is to say, with proper design and operation of a DPIV system, the DPIV data could be processed according to the proposed method to obtain particle sizes in addition to particle velocities. As an additional benefit, one could then compute the mass flux of the entrained particles from the particle sizes and velocities. As in DPIV as practiced heretofore, a pulsed laser beam would be formed into a thin sheet to illuminate a plane of interest in a flow field and the illuminated plane would be observed by means of a charge-coupled device (CCD) camera aimed along a line perpendicular to the illuminated plane. Unlike in DPIV as practiced heretofore, care would be taken to polarize the laser beam so that its electric field would lie in the illuminated plane, for the reason explained in the next paragraph. The proposed method applies, more specifically, to transparent or semitransparent spherical particles that have an index of refraction different from that of the fluid in which they are entrained. The method is based on the established Mie theory, which describes the scattering of light by diffraction, refraction, and specular reflection of light by such particles. In the case of a particle illuminated by polarized light and observed in the arrangement described in the preceding paragraph, the Mie theory shows that the image of the particle on the focal plane of the CCD camera includes two glare spots: one attributable to light reflected toward the camera and one attributable to light refracted toward the camera. The distance between the glare spots is a known function of the size of the particle, the indices of refraction of the particle material, and design parameters of the camera optics. Hence, the size of a particle can be determined from the distance between the glare spots. The proposed method would be implemented in an algorithm that would automatically identify, and measure the distance between, the glare spots for each particle for which a suitable image has been captured in a DPIV image frame. The algorithm (see figure) would begin with thresholding of data from the entire image frame to reduce noise, thereby facilitating discrimination of particle images from the background and aiding in the separation of overlapping particles. It is important not to pick a threshold level so high that the light intensity between a given pair of glare spots does not fall below the threshold value, leaving the glare spots disconnected. The image would then be scanned in a sequence of rows and columns of pixels to identify groups of adjacent pixels that contain nonzero brightnesses and that are surrounded by pixels of zero brightness. Each such group would be assumed to constitute the image of one particle. Each such group would be further analyzed to determine whether the image was saturated; saturated particle images must be rejected because the locations of glare spots in saturated images cannot accurately be determined. Within each unsaturated particle image, the centroids (deemed to be the locations) of the glare spots would be determined by means of gradients of brightness distributions and three-point horizontal and three-point vertical Gaussian estimates based on the brightness values of the brightest pixels and the pixels adjacent to them. If the brightness of a given particle image contained only one peak, then it would be assumed that a second glare spot did not exist and that image would be rejected.

Wernet, M. P.↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

DAQExpert the service to increase CMS data-taking efficiency

The Data Acquisition (DAQ) system of the Compact Muon Solenoid (CMS) experiment at the LHC is a complex system responsible for the data readout, event building and recording of accepted events. Its proper functioning plays a critical role in the data-taking efficiency of the CMS experiment. In order to ensure high availability and recover promptly in the event of hardware or software failure of the subsystems, an expert system, the DAQ Expert, has been developed. It aims at improving the data taking efficiency, reducing the human error in the operations and minimising the on-call expert demand. Introduced in the beginning of 2017, it assists the shift crew and the system experts in recovering from operational faults, streamlining the post mortem analysis and, at the end of Run 2, triggering fully automatic recovery without human intervention. DAQ Expert analyses the real-time monitoring data originating from the DAQ components and the high-level trigger updated every few seconds. It pinpoints data flow problems, and recovers them automatically or after given operator approval. We analyse the CMS downtime in the 2018 run focusing on what was improved with the introduction of automated recovery; present challenges and design of encoding the expert knowledge into automated recovery jobs. Furthermore, we demonstrate the web-based, ReactJS interfaces that ensure an effective cooperation between the human operators in the control room and the automated recovery system. We report on the operational experience with automated recovery.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Implementation of ATLAS Distributed Computing monitoring dashboards using InfluxDB and Grafana

For the last 10 years, the ATLAS Distributed Computing project has based its monitoring infrastructure on a set of custom designed dashboards provided by CERN. This system functioned very well for LHC Runs 1 and 2, but its maintenance has progressively become more difficult and the conditions for Run 3, starting in 2021, will be even more demanding; hence a more standard code base and more automatic operations are needed. A new infrastructure has been provided by CERN, based on InfluxDB as the data store and Grafana as the display environment. ATLAS has adapted and further developed its monitoring tools to use this infrastructure for data and workflow management monitoring and accounting dashboards, expanding the range of previous possibilities with the aim to achieve a single, simpler, environment for all monitoring applications. This document describes these tools and the data flows for monitoring and accounting.

97 MATHEMATICS AND COMPUTING↗

Concept of Operations of Next-Generation Traffic Control Utilizing Infrastructure-Based Cooperative Perception

This paper provides a system architecture for an infrastructure-based cooperative perception fusion engine for next-generation traffic control. This engine will provide a complete state-space digital representation with measurable accuracy to support a wide-range of applications. The architecture includes inputs, functional flow, data standardization recommendations, outputs, and supported applications. The cooperative perception engine addresses critical needs with respect to accelerating the benefits of automation through intelligent roadway infrastructure, which complements and accelerates connected and automated vehicle (CAV) technology. The cooperative perception acquires and fuses information from sensors (radar, LiDAR, and cameras) and CAVs to perceive roadway traffic states of moving objects, creates a complete 3D digital representation of that state-space, and communicates it to downstream application such as intelligent signal control, safety and energy applications, and cooperate driving applications. The intelligent roadway infrastructure approach, as opposed to a vehicle-centric approach, is more scalable because it can be deployed to the roughly 300,000 signalized intersections more readily than over 300 million vehicles in the United States, and accrues early-stage benefits equitable to all roadway users addressing safety, equity, fuel efficiency, and greenhouse gas reduction.

ADVANCED PROPULSION SYSTEMS↗