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

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Predicting Instability and the Effect of Wind Loading on Single-Axis Trackers

As PV modules continue to trend toward larger, thinner, and more flexible forms they grow more susceptible to damage from dynamic wind loading. As a result, understanding the impact of wind on PV systems, particularly when mounted on solar-tracking hardware, and identifying robust, stable array layouts and stow strategies is becoming increasingly important for the PV community. In our ongoing DuraMAT project, we are developing an open-source software package, PVade (PV aerodynamic design engineering), to simulate the cascading fluid-structure interaction that occurs within solar-tracking arrays to enable researchers to test hardware, layout, and tracker control changes, leading to enhanced stability and a reduction in wind-driven damage. We will give an overview of the PVade software, highlighting recent user-interface and algorithm developments, before presenting the latest outcomes from our ongoing validation campaign in which we analyze and compare with experimental data obtained from a DuraMAT 1 project. From there, we will present simulated results from a larger, multi-row array and highlight relationships between varying tracker angles and stability as measured by different experimentally validated metrics.

fluid structure interaction↗
DOE OSTI2020

A general-purpose method for Pareto optimal placement of flow rate and concentration sensors in networked systems – With application to wastewater treatment plants

The advent of affordable computing, low-cost sensor hardware, and high-speed and reliable communications have spurred installation of ubiquitous sensors in complex engineered systems. However, ensuring reliable data quality remains a challenge. Exploitation of redundancy among sensor signals can help improving the precision of measured variables, detecting the presence of gross errors, and identifying faulty sensors. The cost of sensor ownership, maintenance efforts in particular, can still be cost-prohibitive however. Maximizing the ability to assess and control data quality while minimizing the cost of ownership thus requires a careful sensor placement. To solve this challenge, in this work we develop a generally applicable method to solve the multi-objective sensor placement problem in systems governed by linear and bilinear balance equations. Importantly, the method computes all Pareto-optimal sensor layouts with conventional computational resources and requires no information about the expected sensor quality.

42 ENGINEERING↗
DOE OSTI2012

Multi-chord fiber-coupled interferometry of supersonic plasma jets (invited)

A multi-chord fiber-coupled interferometer is being used to make time-resolved density measurements of supersonic argon plasma jets on the Plasma Liner Experiment. The long coherence length of the laser (>10 m) allows signal and reference path lengths to be mismatched by many meters without signal degradation, making for a greatly simplified optical layout. Measured interferometry phase shifts are consistent with a partially ionized plasma in which both positive and negative phase shift values are observed depending on the ionization fraction. In this case, both free electrons and bound electrons in ions and neutral atoms contribute to the index of refraction. This paper illustrates how the interferometry data, aided by numerical modeling, are used to derive total jet density, jet propagation velocity ({approx}15-50 km/s), jet length ({approx}20-100 cm), and 3D expansion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Streaming Data Reorganization at Scale with DeltaFS Indexed Massive Directories

We report complex storage stacks providing data compression, indexing, and analytics help leverage the massive amounts of data generated today to derive insights. It is challenging to perform this computation, however, while fully utilizing the underlying storage media. This is because, while storage servers with large core counts are widely available, single-core performance and memory bandwidth per core grow slower than the core count per die. Computational storage offers a promising solution to this problem by utilizing dedicated compute resources along the storage processing path. We present DeltaFS Indexed Massive Directories (IMDs), a new approach to computational storage. DeltaFS IMDs harvest available (i.e., not dedicated) compute, memory, and network resources on the compute nodes of an application to perform computation on data. We demonstrate the efficiency of DeltaFS IMDs by using them to dynamically reorganize the output of a real-world simulation application across 131,072 CPU cores. DeltaFS IMDs speed up reads by 1,740x while only slightly slowing down the writing of data during simulation I/O for in situ data processing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

A system-level cost-of-energy wind farm layout optimization with landowner modeling

This work applies an enhanced levelized wind farm cost model, including landowner remittance fees, to determine optimal turbine placements under three landowner participation scenarios and two land-plot shapes. Instead of assuming a continuous piece of land is available for the wind farm construction, as in most layout optimizations, the problem formulation represents landowner participation scenarios as a binary string variable, along with the number of turbines. The cost parameters and model are a combination of models from the National Renewable Energy Laboratory (NREL), Lawrence Berkeley National Laboratory, and Windustiy. The system-level cost-of-energy (COE) optimization model is also tested under two land-plot shapes: equally-sized square land plots and unequal rectangle land plots. The optimal COEs results are compared to actual COE data and found to be realistic. The results show that landowner remittances account for approximately 10% of farm operating costs across all cases. Irregular land-plot shapes are easily handled by the model. We find that larger land plots do not necessarily receive higher remittance fees. The model can help site developers identify the most crucial land plots for project success and the optimal positions of turbines, with realistic estimates of costs and profitability. (C) 2013 Elsevier Ltd. All rights reserved.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Conducting a Nuclear Security Assessment

There are three general steps that make up a nuclear security assessment: 1. Develop data Libraries that indicate how effective the physical protection measures are both individually but also as parts of subsystems and actual systems. 2. Perform Path Analysis 3. Perform Scenario Analysis. Depending upon the nature and objectives of the assessment not all three of these steps may need to be performed; for example, at facilities with simple layouts there may not be a need to perform path analysis. Each of these steps is described within this report.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Characterisations of the HinOTORI telescope with a three-color imager at Ali Observatory in Western Tibet

HinOTORI is a new telescope supported by an international collaboration project between China and Japan. It is a 50 centimeter telescope equipped with simultaneous three-color imagers (u',R C , and I C bands). It is located at Ali Observatory at an altitude of 5100m. Thanks to the high altitude and extreme dryness, Ali site is one of the most suitable sites for optical astrometry. HinOTORI telescope aims at detecting optical transients such as the counterparts of gravitational wave (GW) sources, supernovae, gamma-ray bursts (GRB) and so on. This paper describes the site information, design of simultaneous three-color optical layout, system instruments and whole control system. We also report some telescope characterisations for three bands (u'/R C /I C ) respectively, such as Hartmann constant (0.49"/0.56"/0.60"), best focus position (3.922/3.920/3.903 mm), PSF FWHM size (3.755/3.328/3.167pixels), total transmittance and limiting magnitude (15.69/17.57/17.05mag, 10 σ 30 seconds exposure time). With different airmass observation data, the atmospheric extinction coefficients of three bands (0.366/0.061/0.026) were also derived.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Understanding Dynamic Model Validation of a Wind Turbine Generator and a Wind Power Plant

Regional reliability organizations require power plants to validate the dynamic models that represent them to ensure that power systems studies are performed to the best representation of the components installed. In the process of validating a wind power plant (WPP), one must be cognizant of the parameter settings of the wind turbine generators (WTGs) and the operational settings of the WPP. Validating the dynamic model of a WPP is required to be performed periodically. This is because the control parameters of the WTGs and the other supporting components within a WPP may be modified to comply with new grid codes or upgrades to the WTG controller with new capabilities developed by the turbine manufacturers or requested by the plant owners or operators. The diversity within a WPP affects the way we represent it in a model. Diversity within a WPP may be found in the way the WTGs are controlled, the wind resource, the layout of the WPP (electrical diversity), and the type of WTGs used. Each group of WTGs constitutes a significant portion of the output power of the WPP, and their unique and salient behaviors should be represented individually. The objective of this paper is to illustrate the process of dynamic model validations of WTGs and WPPs, the available data recorded that must be screened before it is used for the dynamic validations, and the assumptions made in the dynamic models of the WTG and WPP that must be understood. Without understanding the correct process, the validations may lead to the wrong representations of the WTG and WPP modeled.

17 WIND ENERGY↗
DOE OSTI2019

Next-Generation Search for Solar Axion Dark Matter with the International Axion Observatory

The International Axion Observatory (IAXO) was first proposed in 2011[1]-[5]. With this proposal our LDRD team, founding member of IAXO has been able to play a leading role in the IAXO experiment. We have participated in technical, scientific and organizational IAXO meetings to shape the future of the experiment. We accomplished the layout of the first-ever full-revolution telescope for solar axion searches[6]-[10] and expanded the science reach of IAXO from standard axion searches to new and potentially more exotic opportunities, such as other dark matter candidates, hidden sector particles or dark energy searches [11]-[20]. We also fulfilled the analysis of axion science data previously collected with the LLNL IAXO pathfinder x-ray telescope (XRT) [21] at the European Organization for Nuclear Research particle physics (CERN) located near Geneva, Switzerland, by means of the CERN Axion Solar Experiment (CAST). Moreover, LDRD PI Dr. Julia K. Vogel has officially been elected as Deputy Spokesperson of IAXO.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Comparison of modular analytical wake models to the Lillgrund wind plant

Efficient and accurate wake models are required for wind plant performance modeling and the suite of engineering processes that support wind plant layout, control, and monitoring. Although many analytical and engineering wake models with low computational costs have been proposed, their ability to represent the power production of large wind plants in a wide range of atmospheric conditions is not completely understood. The following validation study reviews the underlying theory for analytical wake models, outlines quality control procedures for observational data, and compares model results with observational data from the Lillgrund Wind Plant. Lillgrund makes a valuable case study for wake modeling because of its regular arrangement and the relatively close spacing of constituent wind turbines, which lead to regular and significant wake interactions within the wind plant and the development of deep array flow conditions. Formulations for the velocity deficit, wake-added turbulence, and wake superposition methods are considered in a modular sense, yielding many possible configurations to represent wind turbine wakes, of which seven are examined in detail. Velocity deficit models that account for flow conditions in the near wake are better able to reproduce power production for wind turbines in the transitional region of the wind plant, where wind turbines experience as many as five wakes from upstream turbines. Finally, in the deep array, where power production reaches asymptotic values and wake statistics become quasi-periodic, wake superposition schemes become the largest driver in error reduction; using the linear or maximum wake superposition methods can reduce the relative root mean square error by as much as 40% in the deep array.

17 WIND ENERGY↗
DOE OSTI2014

Scaling Graph Community Detection on the Tilera Many-core Architecture

In an era when power constraints and data movement are proving to be significant barriers for the application of high-end computing, the Tilera many-core architecture offers a low-power platform exhibiting many important characteristics of future systems, including a large number of simple cores, a sophisticated network-on-chip, and fine-grained control over memory and caching policies. While this emerging architecture has been previously studied for structured compute-intensive kernels, benchmarking the platform for data-bound, irregular applications present significant challenges that have remained unexplored. Community detection is an advanced prototypical graph-theoretic operation with applications in numerous scientific domains including life sciences, cyber security, and power systems. In this work, we explore multiple design strategies toward developing a scalable tool for community detection on the Tilera platform. Using several memory layout and work scheduling techniques we demonstrate speedups of up to 46x on 36 cores of the Tilera TileGX36 platform over the best serial implementation, and also show results that have comparable quality and performance to mainstream x86 platforms. To the best of our knowledge this is the first work addressing graph algorithms on the Tilera platform. This study demonstrates that through careful design space exploration, low-power many-core platforms like Tilera can be effectively exploited for graph algorithms that that embody all the essential characteristics of an irregular application.

community detection↗
DOE OSTI2023

Accelerating Random Forest Classification on GPU and FPGA

Random Forests (RFs) are a commonly used machine learning method for classification and regression tasks spanning a variety of application domains, including bioinformatics, business analytics, and software optimization. While prior work has focused primarily on improving performance of the training of RFs, many applications, such as malware identification, cancer prediction, and banking fraud detection, require fast RF classification. In this work, we accelerate RF classification on GPU and FPGA. In order to provide efficient support for large datasets, we propose a hierarchical memory layout suitable to the GPU/FPGA memory hierarchy. We design three RF classification code variants based on that layout, and we investigate GPU- and FPGA-specific considerations for these kernels. Our experimental evaluation, performed on an Nvidia Xp GPU and on a Xilinx Alveo U250 FPGA accelerator card using publicly available datasets on the scale of millions of samples and tens of features, covers various aspects. First, we evaluate the performance benefits of our hierarchical data structure over the standard compressed sparse row (CSR) format. Second, we compare our GPU implementation with cuML, a machine learning library targeting Nvidia GPUs. Third, we explore the performance/accuracy tradeoff resulting from the use of different tree depths in the RF. Finally, we perform a comparative performance analysis of our GPU and FPGA implementations. Our evaluation shows that for high accuracy targets, our GPU implementation yields 5-9x speedup over CSR, and up to a 2x speedup over cuML.

FPGA, Xilinx FPGA, GPU, Random Forest classificati↗
DOE OSTI2015

Stationary Liquid Fuel Fast Reactor

For effective burning of hazardous transuranic (TRU) elements of used nuclear fuel, a transformational advanced reactor concept named SLFFR (Stationary Liquid Fuel Fast Reactor) was proposed based on stationary molten metallic fuel. The fuel enters the reactor vessel in a solid form, and then it is heated to molten temperature in a small melting heater. The fuel is contained within a closed, thick container with penetrating coolant channels, and thus it is not mixed with coolant nor flow through the primary heat transfer circuit. The makeup fuel is semi- continuously added to the system, and thus a very small excess reactivity is required. Gaseous fission products are also removed continuously, and a fraction of the fuel is periodically drawn off from the fuel container to a processing facility where non-gaseous mixed fission products and other impurities are removed and then the cleaned fuel is recycled into the fuel container. A reference core design and a preliminary plant system design of a 1000 MWt TRU- burning SLFFR concept were developed using TRU-Ce-Co fuel, Ta-10W fuel container, and sodium coolant. Conservative design approaches were adopted to stay within the current material performance database. Detailed neutronics and thermal-fluidic analyses were performed to develop a reference core design. Region-dependent 33-group cross sections were generated based on the ENDF/B-VII.0 data using the MC2-3 code. Core and fuel cycle analyses were performed in theta-r-z geometries using the DIF3D and REBUS-3 codes. Reactivity coefficients and kinetics parameters were calculated using the VARI3D perturbation theory code. Thermo-fluidic analyses were performed using the ANSYS FLUENT computational fluid dynamics (CFD) code. Figure 0.1 shows a schematic radial layout of the reference 1000 MWt SLFFR core, and Table 0.1 summarizes the main design parameters of SLFFR-1000 loop plant. The fuel container is a 2.5 cm thick cylinder with an inner radius of 87.5 cm. The fuel container is penetrated by twelve hexagonal control assembly (CA) guide tubes, each of which has 3.0 mm thickness and 69.4 mm flat-to-flat outer distance. The distance between two neighboring CA guide tube is selected to be 26 cm to provide an adequate space for CA driving systems. The fuel container has 18181 penetrating coolant tubes of 6.0 mm inner diameter and 2.0 mm thickness. The coolant tubes are arranged in a triangular lattice with a lattice pitch of 1.21 cm. The fuel, structure, and coolant volume fractions inside the fuel container are 0.386, 0.383, and 0.231, respectively. Separate steel reflectors and B4C shields are used outside of the fuel container. Six gas expansion modules (GEMs) of 5.0 cm thickness are introduced in the radial reflector region. Between the radial reflector and the fuel container is a 2.5 cm sodium gap. The TRU inventory at the beginning of equilibrium cycle (BOEC) is 5081 kg, whereas the TRU inventory at the beginning of life (BOL) was 3541 kg. This is because the equilibrium cycle fuel contains a significantly smaller fissile fraction than the LWR TRU feed. The fuel inventory at BOEC is composed of 34.0 a/o TRU, 41.4 a/o Ce, 23.6 a/o Co, and 1.03 a/o solid fission products. Since uranium-free fuel is used, a theoretical maximum TRU consumption rate of 1.011 kg/day is achieved. The semi-continuous fuel cycle based on the 300-batch, 1- day cycle approximation yields a burnup reactivity loss of 26 pcm/day, and requires a daily reprocessing of 32.5 kg of SLFFR fuel. This yields a daily TRU charge rate of 17.45 kg, including a makeup TRU feed of 1.011 kg recovered from the LWR used fuel. The charged TRU-Ce-Co fuel is composed of 34.4 a/o TRU, 40.6 a/o Ce, and 25.0 a/o Co.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Low-cost sensor-based damage localization for large-area monitoring of FRP composites

Abstract In recent years, there has been growing interest in self-sensing structural materials across research and industry sectors. Detecting and locating structural damage typically requires numerous sensors wired to a data acquisition (DAQ) circuit, rendering implementation impractical in real structures. This paper proposes an innovative, cost-effective sensor network for damage detection and localization in fiber-reinforced polymer composites. The innovation encompasses three key elements: (1) utilizing carbon fiber tows within the composite as piezoresistive sensors, eliminating the need for additional foreign sensor devices; (2) introducing a novel sensor layout wherein sensor tow branches with varied resistance values are connected in parallel, reducing the number of connections to the DAQ circuit and cutting manufacturing costs significantly; (3) developing a practical sensor terminal fabrication technique to minimize manufacturing expenses. The proposed design methodology for the branch resistance values is first validated using a demonstration panel. Subsequently, the overall strategy is assessed by conducting impact tests on carbon and glass fiber-reinforced composite specimens. Results validate the sensor’s ability to accurately detect and locate structural damage.

Demo, Luke B. (ORCID:0000000208806522)↗
DOE OSTI2013

Jefferson Laboratory Hall A SuperBigBite Spectrometer Data Acquisition System

The SuperBigBite detector is a large acceptance spectrometer which is being built for Hall A at Jefferson Laboratory and planned for completion in 2017. Several experiments are approved for this detector ranging from form factors to nucleon structure. The detector consists mainly of a large dipole magnet and several plane of Gas Electron Multiplier trackers associated with calorimeters. In order to reduce the cost of the project the electronics used will be a mix of older Fastbus and newly developed electronics. I will present the layout of the system and how we plan to handle the high background rates seen by the different detectors for the different experiments.

Camsonne, Alexandre↗
DOE OSTI2012

Hybrid AI/Cognitive Tactical Behavior Framework for LVC (LDRD Project Final Report)

This Lab-Directed Research and Development (LDRD) sought to develop technology that enhances scenario construction speed, entity behavior robustness, and scalability in Live-Virtual-Constructive (LVC) simulation. We investigated issues in both simulation architecture and behavior modeling. We developed path-planning technology that improves the ability to express intent in the planning task while still permitting an efficient search algorithm. An LVC simulation demonstrated how this enables 'one-click' layout of squad tactical paths, as well as dynamic re-planning for simulated squads and for real and simulated mobile robots. We identified human response latencies that can be exploited in parallel/distributed architectures. We did an experimental study to determine where parallelization would be productive in Umbra-based force-on-force (FOF) simulations. We developed and implemented a data-driven simulation composition approach that solves entity class hierarchy issues and supports assurance of simulation fairness. Finally, we proposed a flexible framework to enable integration of multiple behavior modeling components that model working memory phenomena with different degrees of sophistication.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

A Reconfigurable Neural Network ASIC for Detector Front-End Data Compression at the HL-LHC

Despite advances in the programmable logic capabilities of modern trigger systems, a significant bottleneck remains in the amount of data to be transported from the detector to off-detector logic where trigger decisions are made. We demonstrate that a neural network (NN) autoencoder model can be implemented in a radiation-tolerant application-specific integrated circuit (ASIC) to perform lossy data compression alleviating the data transmission problem while preserving critical information of the detector energy profile. For our application, we consider the high-granularity calorimeter from the Compact Muon Solenoid (CMS) experiment at the CERN Large Hadron Collider. The advantage of the machine learning approach is in the flexibility and configurability of the algorithm. By changing the NN weights, a unique data compression algorithm can be deployed for each sensor in different detector regions and changing detector or collider conditions. To meet area, performance, and power constraints, we perform quantization-aware training to create an optimized NN hardware implementation. The design is achieved through the use of high-level synthesis tools and the hls4ml framework and was processed through synthesis and physical layout flows based on a low-power (LP)-CMOS 65-nm technology node. The flow anticipates 200 Mrad of ionizing radiation to select gates and reports a total area of 3.6 mm 2 and consumes 95 mW of power. The simulated energy consumption per inference is 2.4 nJ. Furthermore, this is the first radiation-tolerant on-detector ASIC implementation of an NN that has been designed for particle physics applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

A Real-Time Vehicle-Specific Eco-Routing Model for On-Board Navigation Applications Capturing Transient Vehicle Behavior

The paper develops a real-time vehicle-specific eco-routing model for use in on-board navigation systems for both conventional fuel- and battery-powered electric vehicles. The model uses a novel link cost function that retains all microscopic transient behavior along a link by capturing within-link speed, acceleration, and road grade variations. Specifically, eight vehicle-agnostic link-specific variables are transmitted to the cloud and fused with information received from other connected vehicles. The fused data are then sent back to the connected vehicles and used to compute vehicle-specific eco-routes (edge computing). The solution produces an energy-efficient dynamic user-equilibrium traffic assignment that is solved incrementally. A numerical experiment is first designed to test the model, demonstrating the benefits associated with vehicle-specific eco-routes compared to those produced by traditional models. The model is then implemented in a micro-simulation framework to evaluate the network-wide impacts of the proposed energy-efficient user-optimum incremental traffic assignment for different traffic demand levels. Results demonstrate that the proposed model produces lower network-wide energy consumption levels compared to traditional energy-efficient and travel time user-optimum traffic assignment methods for both conventional fuel and electric vehicles. Conventional fuel savings relative to travel time routing decrease with increasing traffic demand levels, while electric power savings do not vary monotonically with congestion levels. Energy savings relative to traditional eco-routing are also demonstrated to not vary monotonically with demand levels. Results of the study also demonstrate that the transportation network layout significantly affects the eco-routing system performance. Finally, the feasibility of the proposed model in real-world applications is discussed and presented.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗