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At least 397 records · Page 22

RApid Blade and Blade-Vortex InTeraction (RABBIT) GUI implementation via MATLAB Application Designer

Rotorcraft noise source identification and reduction is crucial to the emergence of the Urban Air Mobility (UAM) market. One key rotor noise source is Blade Vortex Interaction (BVI), caused by the rotor wake interacting with the rotor blades. The low-fidelity RApid Blade and Blade-Vortex InTeraction (RABBIT) tool was created to predict the location and characteristics of Blade-Vortex Interaction (BVI) noise. RABBIT enables engineers to quickly locate and understand designs or configurations that cause significant BVI noise. Furthermore, RABBIT can identify the time and location of blade overlap for coaxial rotors. RABBIT is not a general acoustic prediction tool, but instead utilizes vortex and wake parameters to visualize and predict only BVI noise. To date, RABBIT has been validated against CAMRAD II and ANOPP2/AARON for three NASA Revolutionary Vertical Lift Technology (RVLT) concept vehicles: the Quiet Single Main Rotor (QSMR), Side-by-Side, and Quadrotor. RABBIT has been shown to be a useful BVI prediction tool capable of visualizing BVI as a function of various parameters. Impulse factor and time rate of change of loading allows for a unique BVI prediction technique that provides information on impulse strength, location, and frequency. This presentation will highlight how MATLAB’s App Designer was utilized to enable users to navigate RABBIT easily and efficiently without prior experience with MATLAB or rotorcraft acoustics. RABBIT users can build and view rotors in real time with options to control blade chord, radius, phasing, and airfoil geometry. Furthermore, multiple rotors can be combined to create state-of-the-art multi-rotor vehicles or fleets. Editable tables, sliding bars, and push buttons were implemented within MATLAB’s App Designer for RABBIT’s GUI to allow engineers and designers to predict low order acoustic impact of BVI occurrences.

Natasha Lydia Schatzman↗

Characterization of the NPOD3 Detectors in MCNP5 and MCNP6

Researchers performed a series of measurements in May 2012 to characterize the NPOD3 detector systems. The detectors were placed in varying states of disassembly to determine the effect of individual components on detection efficiency. A 4.5 kg α-phase Pu sphere known as the Los Alamos BeRP Ball was used as the SNM source in both a bare configuration and reflected by varying thicknesses of polyethylene. A set of simulations matching the experimental setups were run and the data were compared to the measured data. The total and leakage multiplication and the inferred k values were determined for both the simulations and the measurements. Table 3 shows a comparison of the results from MCNP6 and MCNP5 with the list-mode patch to the measured results. The count rates for the calculated results were obtained by dividing the total line count in the list-mode file (equivalent to the total number of absorptions in the NPOD detectors) by the total run time. The count rates are identical for both codes, and they both produce the same multiplicity and inferred k values regardless of measurement time as expected.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

QuakeSim 2.0

QuakeSim 2.0 improves understanding of earthquake processes by providing modeling tools and integrating model applications and various heterogeneous data sources within a Web services environment. QuakeSim is a multisource, synergistic, data-intensive environment for modeling the behavior of earthquake faults individually, and as part of complex interacting systems. Remotely sensed geodetic data products may be explored, compared with faults and landscape features, mined by pattern analysis applications, and integrated with models and pattern analysis applications in a rich Web-based and visualization environment. Integration of heterogeneous data products with pattern informatics tools enables efficient development of models. Federated database components and visualization tools allow rapid exploration of large datasets, while pattern informatics enables identification of subtle, but important, features in large data sets. QuakeSim is valuable for earthquake investigations and modeling in its current state, and also serves as a prototype and nucleus for broader systems under development. The framework provides access to physics-based simulation tools that model the earthquake cycle and related crustal deformation. Spaceborne GPS and Inter ferometric Synthetic Aperture (InSAR) data provide information on near-term crustal deformation, while paleoseismic geologic data provide longerterm information on earthquake fault processes. These data sources are integrated into QuakeSim's QuakeTables database system, and are accessible by users or various model applications. UAVSAR repeat pass interferometry data products are added to the QuakeTables database, and are available through a browseable map interface or Representational State Transfer (REST) interfaces. Model applications can retrieve data from Quake Tables, or from third-party GPS velocity data services; alternatively, users can manually input parameters into the models. Pattern analysis of GPS and seismicity data has proved useful for mid-term forecasting of earthquakes, and for detecting subtle changes in crustal deformation. The GPS time series analysis has also proved useful as a data-quality tool, enabling the discovery of station anomalies and data processing and distribution errors. Improved visualization tools enable more efficient data exploration and understanding. Tools provide flexibility to science users for exploring data in new ways through download links, but also facilitate standard, intuitive, and routine uses for science users and end users such as emergency responders.

Donnellan, Andrea↗

Secure Interoperable Open Smart Grid Demonstration Project

The Consolidated Edison, Inc., of New York (Con Edison) Secure Interoperable Open Smart Grid Demonstration Project (SGDP), sponsored by the United States (US) Department of Energy (DOE), demonstrated that the reliability, efficiency, and flexibility of the grid can be improved through a combination of enhanced monitoring and control capabilities using systems and resources that interoperate within a secure services framework. The project demonstrated the capability to shift, balance, and reduce load where and when needed in response to system contingencies or emergencies by leveraging controllable field assets. The range of field assets includes curtailable customer loads, distributed generation (DG), battery storage, electric vehicle (EV) charging stations, building management systems (BMS), home area networks (HANs), high-voltage monitoring, and advanced metering infrastructure (AMI). The SGDP enables the seamless integration and control of these field assets through a common, cyber-secure, interoperable control platform, which integrates a number of existing legacy control and data systems, as well as new smart grid (SG) systems and applications. By integrating advanced technologies for monitoring and control, the SGDP helps target and reduce peak load growth, improves the reliability and efficiency of Con Edison’s grid, and increases the ability to accommodate the growing use of distributed resources. Con Edison is dedicated to lowering costs, improving reliability and customer service, and reducing its impact on the environment for its customers. These objectives also align with the policy objectives of New York State as a whole. To help meet these objectives, Con Edison’s long-term vision for the distribution grid relies on the successful integration and control of a growing penetration of distributed resources, including demand response (DR) resources, battery storage units, and DG. For example, Con Edison is expecting significant long-term growth of DG. The SGDP enables the efficient, flexible integration of these disparate resources and lays the architectural foundations for future scalability. Con Edison assembled an SGDP team of more than 16 different project partners, including technology vendors, and participating organizations, and the Con Edison team provided overall guidance and project management. Project team members are listed in Table 1-1.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes: A Recursive Maximum Likelihood Decoding - Part 3

The Viterbi algorithm is indeed a very simple and efficient method of implementing the maximum likelihood decoding. However, if we take advantage of the structural properties in a trellis section, other efficient trellis-based decoding algorithms can be devised. Recently, an efficient trellis-based recursive maximum likelihood decoding (RMLD) algorithm for linear block codes has been proposed. This algorithm is more efficient than the conventional Viterbi algorithm in both computation and hardware requirements. Most importantly, the implementation of this algorithm does not require the construction of the entire code trellis, only some special one-section trellises of relatively small state and branch complexities are needed for constructing path (or branch) metric tables recursively. At the end, there is only one table which contains only the most likely code-word and its metric for a given received sequence r = (r(sub 1), r(sub 2),...,r(sub n)). This algorithm basically uses the divide and conquer strategy. Furthermore, it allows parallel/pipeline processing of received sequences to speed up decoding.

Lin, Shu↗

Infrastructure development assistance modeling for nuclear power plant

The purpose of this paper is to develop a model, a general frame to be utilized in assisting newcomer countries to start a nuclear power program. A nuclear power plant project involves technical complexity and high level of investment with long duration. Considering newcomers are mostly developing countries that lack the national infrastructure, key infrastructure issues may constitute the principal constraints to the development of a nuclear power program. In this regard, it is important to provide guidance and support to set up an appropriate infrastructure when we help them with the first launch of nuclear power plant project. To date, as a sole nuclear power generation company, KHNP has been invited many times to mentor or assist newcomer countries for their successful start of a nuclear power program since Republic of Korea is an exemplary case of a developing country which began nuclear power program from scratch and became a major world nuclear energy country in a short period of time. Through hosting events organized to aid newcomer countries' initiation of nuclear power projects, difficulties have been recognized. Each event had different contents according to circumstances because they were held as an unstructured and one-off thing. By developing a general model, we can give more adequate and effective aid in an efficient way. In this paper, we created a model to identify necessary infrastructures at the right stage, which was mainly based on a case of Korea. Taking into account the assistance we received from foreign companies and our own efforts for technological self-reliance, we have developed a general time table and specified activities required to do at each stage. From a donor's perspective, we explored various ways to help nuclear infrastructure development including technical support programs, training courses, and participating in IAEA technical cooperation programs on a regular basis. If we further develop the model, the next task would be to make the model more sophisticated as a 'semi-tailored model' so that it can be applied to a certain country reflecting its unique conditions. In accordance with its degree of established infrastructure, we can adjust or modify the model. Despite lots of benefits of using this model, there remain limitations such as time and budget constraints. These problems, however, can be addressed by cooperating with international organization such as the IAEA and other companies that share the same goal of helping newcomer countries introduce nuclear power. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Distillation Column Flooding Predictor

The Flooding Predictor™ is a patented advanced control technology proven in research at the Separations Research Program, University of Texas at Austin, to increase distillation column throughput by over 6%, while also increasing energy efficiency by 10%. The research was conducted under a U. S. Department of Energy Cooperative Agreement awarded to George Dzyacky of 2ndpoint, LLC. The Flooding Predictor™ works by detecting the incipient flood point and controlling the column closer to its actual hydraulic limit than historical practices have allowed. Further, the technology uses existing column instrumentation, meaning no additional refining infrastructure is required. Refiners often push distillation columns to maximize throughput, improve separation, or simply to achieve day-to-day optimization. Attempting to achieve such operating objectives is a tricky undertaking that can result in flooding. Operators and advanced control strategies alike rely on the conventional use of delta-pressure instrumentation to approximate the column’s approach to flood. But column delta-pressure is more an inference of the column’s approach to flood than it is an actual measurement of it. As a consequence, delta pressure limits are established conservatively in order to operate in a regime where the column is never expected to flood. As a result, there is much “left on the table” when operating in such a regime, i.e. the capacity difference between controlling the column to an upper delta-pressure limit and controlling it to the actual hydraulic limit. The Flooding Predictor™, an innovative pattern recognition technology, controls columns at their actual hydraulic limit, which research shows leads to a throughput increase of over 6%. Controlling closer to the hydraulic limit also permits operation in a sweet spot of increased energy-efficiency. In this region of increased column loading, the Flooding Predictor is able to exploit the benefits of higher liquid/vapor traffic that produce increased contact area and lead to substantial increases in separation efficiency – which translates to a 10% increase in energy efficiency on a BTU/bbl basis. The Flooding Predictor™ operates on the principle that between five to sixty minutes in advance of a flooding event, certain column variables experience an oscillation, a pre-flood pattern. The pattern recognition system of the Flooding Predictor™ utilizes the mathematical first derivative of certain column variables to identify the column’s pre-flood pattern(s). This pattern is a very brief, highly repeatable, simultaneous movement among the derivative values of certain column variables. While all column variables experience negligible random noise generated from the natural frequency of the process, subtle pre-flood patterns are revealed among sub-sets of the derivative values of column variables as the column approaches its hydraulic limit. The sub-set of column variables that comprise the pre-flood pattern is identified empirically through in a two-step process. First, 2ndpoint’s proprietary off-line analysis tool is used to mine historical data for pre-flood patterns. Second, the column is flood-tested to fine-tune the pattern recognition for commissioning. Then the Flooding Predictor™ is implemented as closed-loop advanced control strategy on the plant’s distributed control system (DCS), thus automating control of the column at its hydraulic limit.

02 PETROLEUM↗

Distant-Atom Mutation for Better Earth-Abundant Light Absorbers: A Case Study of Cu 2 BaSnSe 4

Thin-film Cu(In,Ga)Se 2 and CdTe solar cells have demonstrated high power conversion efficiencies, but they cannot provide a sustainable clean energy pathway because of the scarcity of Te and In. In this paper, we propose a distant-atom concept to mutate In by a group II element (Ba) and a group IV element (Sn) that are at rather different locations on the periodic table. Because of the very different electronic properties between the cations, the resultant earth-abundant orthorhombic Cu 2 BaSnSe 4 absorber does not have the detrimental cation–cation disorder issue seen in the earth-abundant kesterite Cu 2 ZnSnSe 4 absorber. We anticipate that Cu 2 BaSnSe 4 solar cells should not have large open-circuit voltage deficits as seen in CuZnSnSe 4 solar cells. Density functional theory calculation of the electronic and defect properties of Cu 2 BaSnSe 4 confirms these expectations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Blockchain-Based Decentralized Data Storage and Access Framework for PingER

The blockchain is an innovative technology which opened doors to new applications for solving numerous problems in distributed environments. In this study, we design a blockchain-based data storage and access framework for PingER (worldwide end-to-end Internet performance measurement project) to remove its total dependence on a centralized repository. We use the permissioned blockchain and Distributed Hash Tables (DHT) for this purpose. In the proposed framework, metadata of the files are stored on the blockchain whereas the actual files are stored off-chain through DHT at multiple locations using a peer-to-peer network of PingER Monitoring Agents. Lastly, this will provide decentralized storage, distributed processing, and efficient lookup capabilities to the PingER framework.

97 MATHEMATICS AND COMPUTING↗

Reservoir Thermal Energy Storage Benchmarking (Rev. 3)

A benchmarking analysis of RTES research funded by GTO through the Beyond Batteries projects was conducted against the ESGC to see where they fit within the identified ESGC Use Cases. The projects were found to advance knowledge in multiple ESGC use cases, either directly or in some cases, indirectly as enabling technologies. This analysis is helpful to understand where RTES and associated research fits into the larger discussion around energy storage technologies. Also, a retrospective analysis of the Beyond Batteries projects was conducted to evaluate what the projects learned and how the results can be applied to advance the value of RTES. Major results of each of the studies are summarized in Table 2. Additionally, a comparative metrics analysis for RTES was completed to understand where RTES lies within the energy storage industry. Metrics for evaluation of RTES and its comparison to other storage technologies were selected and ranges of their values compiled. The selected metrics – LCOE (levelized cost of energy), capital costs, roundtrip efficiency, energy storage capacity, and storage time – were chosen based on data availability and have a particularly strong influence on the potential deployment of a storage technology. Charts which compare the metrics are presented in section 4.3 and show ranges for each of the 10 selected technologies. However, due to a lack of domestic operational facilities, values for RTES and for portions of the remaining technologies are based on theoretical modeling and studies of best-case scenarios. LCOE estimates for RTES fall within the lower reaches of Figure 15, but nevertheless amount to 2 – 5 times the ESGC Roadmap goal for LCOE, for example in the Facilitating and Evolving Grid Use Case. Capital costs for RTES sit on the higher end (Figure 16) but are expected to decrease as new projects are developed and the technology is refined. The theoretical roundtrip efficiency reported for RTES varies from mid to high percentages (Figure 17) with efficiencies upwards of 93% in modeled scenarios in the Portland Basin (Bershaw et al.,2020). RTES is also expected to have the largest energy storage capacities and longest storage times, likely matched only by lower efficiency hydrogen storage. To better assess the role that RTES could play in energy storage we examined it’s potential in the U.S. The potential depends on many factors. Recently, many researchers have started looking at deep sedimentary basins, depleted oil and gas fields, and basalt formations as potential targets for RTES development. The United States Geological Survey (USGS) has analyzed various cities and shown substantial RTES potential in the cooling sector (Pepin et al., 2021). By modeling RTES in low-quality groundwater (e.g., brackish), it is shown to be favorable across the U.S. with particular suitability in the Illinois Basin, Coastal Plains, and Basin and Range regions. Seasonal RTES operations have also been modeled in the Portland Basin by those at the USGS and Portland State University to simulate an RTES system supplying heating loads needed for the Oregon Health and Science University. Simulations suggest that high conductive heat loss in the initial years exists but tends to decrease with increasing time and development of the resource due to self-insulating nature of the basalts (Burns et al., 2020). Other national laboratory efforts are taking a close look at many of the technical issues involved with RTES (McLing et al., 2019, McLing et al., 2022). These include difficulties in understanding geochemical, hydrogeological, mechanical, and microbiological changes at such elevated temperatures and operational scenarios. Major gaps in research are identified and suggested for future work. With this increased focus to understand how to make RTES successful in the U.S., this technology could be a potential solution to many of the nation’s energy storage problems. For the energy independence of this country, the DOE should prioritize de-risking this technology by making future investments in pilot-scale demonstrations to attract potential investors.

15 GEOTHERMAL ENERGY↗

Retro-Commissioning Sensor Suitcase

This software package is the Graphic User Interface (GUI) software component for the Sensor Suitcase Retro-Commissioning project, which is a sensor and analysis system to support monitoring-based retro-commissioning of small commercial buildings, performed by non-experts. Small commercial buildings typically do not have the budgets or business economics to allow investing in energy efficiency enhancements the building retro-commissioning provides. In addition, they do not have in-house staff with expertise in building systems who can perform building retro-commissioning or identify energy efficiency improvement opportunities. The solution to this problem is to develop a turn-key hardware/software solution (the RCx Sensor Suitcase) that can be used by non-experts to automatically generate low and no-cost energy efficiency rec commendations that will improve building operating costs, occupant comfort and building energy performance. This is a joint project between Lawrence Berkeley National Laboratory, leading the development of the software and analysis elements, and Pacific Northwest National Laboratory (PNNL), leading the development of the hardware and sensor elements with an associated table-based configuration support tool. The project is funded by the U.S. Department of Energy. This software package was developed as a proof-of-concept prototype for the sensor suitcase software component. The software component was developed with a Microsoft Excel spreadsheet which reads the sensor data and calls a MATLAB DLL to analyze the sensor data.

Lin, Guanjing↗

Efficient optimization of integrated aerodynamic-structural design

Techniques for reducing the computational complexity of multidisciplinary design optimization (DO) of aerodynamic structures are described and demonstrated. The basic principles of aerodynamic and structural DO are reviewed; the formulation of the combined DO problem is outlined; and particular attention is given to (1) the application of perturbation methods to cross-sensitivity computations and (2) numerical approximation procedures. Trial DOs of a simple sailplane design are presented in tables and graphs and discussed in detail. The IBM 3090 CPU time for the entire integrated DO was reduced from an estimated 10 h to about 6 min.

Haftka, R. T.↗

TEAMER: Sandia and CalWave Torque Spring Assessment

Power-take-off (PTO) systems for wave energy converters (WEC) require restoring forces for efficient hydrodynamic as well as mechanical to electric power transfer. Implementation of an effective spring mechanism that can provide a restoring torque on e.g. a rotational, winch type PTO shaft is challenging. SNL in collaboration with CalWave, will use numerical finite element simulations to study application of mechanical torsion springs as a highly efficient restoring force element for CalWave's rotational PTO. Material studies will include common steel as a baseline and potentially advanced materials such as fiber composite materials with different cross-sectional profiles. Test report including description and results of FEA (finite element analysis) models. Excel sheet summarizes which scripts were used for which tables and figures in the report. Part of TEAMER request for technical support (RFTS 1) award to CalWave and Sandia National Lab (SNL).

16 TIDAL AND WAVE POWER↗

Status of the NEXT Ion Thruster Long Duration Test

The status of NASA's Evolutionary Xenon Thruster (NEXT) Long Duration Test (LDT) is presented. The test will be conducted with a 36 cm diameter engineering model ion thruster, designated EM3, to validate and qualify the NEXT thruster propellant throughput capability of 450 kg xenon. The ion thruster will be operated at various input powers from the NEXT throttle table. Pretest performance assessments demonstrated that EM3 satisfies all thruster performance requirements. As of June 26, 2005, the ion thruster has accumulated 493 hours of operation and processed 10.2 kg of xenon at a thruster input power of 6.9 kW. Overall ion thruster performance, which includes thrust, thruster input power, specific impulse, and thrust efficiency, has been steady to date with very little variation in performance parameters.

Frandina, Michael M.↗

Energy-efficient specialization of functional units in a Coarse-Grained Reconfigurable Array

Functional units provide the backbone of any spatial accelerator by providing the computing resources. The desire for having rich and expensive functional units is in tension with producing a regular and energy-efficient computing fabric. This paper explores the design trade-off between complex, universal functional units and simpler, limited functional units. We show that a modest amount of specialization reduces the area-delay-energy product of an optimized architecture to 0.86x a baseline architecture. Furthermore, we provide a design guideline that allows an architect to customize the contents of the computing fabric just by examining the profile of benchmarks within the application domains. Functional units are the core of compute-intensive spatial accelerators. They perform the computation of interest with support from local storage and communication structures. Ideally, the functional units will provide rich functionality, supporting operations ranging from simple addition, to fused multiply-adds, to advanced transcendental functions and domain specific operations like add-compare-select. However, the total opportunity cost to support the more complex operations is a function of the cost of the hardware, the rate of occurrence of the operation in the application domain, and the inefficiency of emulating the operation with simpler operators. Examples of operations that are typically emulated in spatial accelerators are division and trigonometric functions, which can be solved using table-lookup based algorithms and the CORDIC algorithm. One reason to avoid having direct hardware support for complex operations in a tiled architecture like a Coarse-Grained Reconfigurable Array (CGRA) is that the expensive hardware will typically need to be replicated in some or all of the architecture's tiles. Tiled architecture are designed such that their tiles are either homogeneous or heterogeneous. Homogeneous architectures are simpler to design but heterogeneous architectures can be more efficient. Generally, CGRAs try to support a rich set of operations with the smallest possible set of hardware devices.

97 MATHEMATICS AND COMPUTING↗

Finite element model for piles in liquefiable ground

This paper develops a three dimensional finite element modelling method for piles in liquefiable ground and applies it to the analysis of seismic pile responses. A unified plasticity model for large post-liquefaction shear deformation of sand provides the basis for the effective and efficient modelling of liquefiable ground. Special attention is dedicated towards the modelling of piles and soil-pile interface to accurately reflect the behaviour of piles. A staged modelling procedure is adopted to appropriately generate the initial conditions for the soil and piles and achieve hydrostatic pore pressure prior to seismic loading. Three centrifuge shaking table tests on single piles, both with and without pile cap and superstructure, in level and inclined liquefiable ground are conducted and simulated in validation and application of the proposed method. Further studies to investigate the effects of pile cap, lateral spreading, and non-liquefiable surface layer are undertaken numerically using the validated method. The results show these aforementioned factors to be influential in the dynamic and residual response of piles in liquefiable ground.

Centrifuge test↗

Spectral scheme for atomic structure calculations in density functional theory

In this study, we present a spectral scheme for atomic structure calculations in pseudopotential Kohn-Sham density functional theory. In particular, after applying an exponential transformation of the radial coordinates, we employ global polynomial interpolation on a Chebyshev grid, with derivative operators approximated using the Chebyshev differentiation matrix, and integrations using Clenshaw-Curtis quadrature. We demonstrate the accuracy and efficiency of the scheme through spin-polarized and unpolarized calculations for representative atoms, while considering local, semilocal, and hybrid exchange-correlation functionals. In particular, we find that $\mathcal{O}$(200) grid points are sufficient to achieve an accuracy of 1 microhartree in the eigenvalues for optimized norm conserving Vanderbilt pseudopotentials spanning the periodic table from atomic number Ζ = 1 to 83.

74 ATOMIC AND MOLECULAR PHYSICS↗

High-Performance Data Analytics Beyond the Relational and Graph Data Models with GEMS

Graphs represent an increasingly popular data model for data-analytics, since they can naturally represent relationships and interactions between entities. Relational databases and their pure table-based data model are not well suitable to store and process sparse data. Consequently, graph databases have gained interest in the last few years and the Resource Description Framework (RDF) became the standard data model for graph data. Nevertheless, while RDF is well suited to analyze the relationships between the entities, it is not efficient in representing their attributes and properties. In this work we propose the adoption of a new hybrid data model, based on attributed graphs, that aims at overcoming the limitations of the pure relational and graph data models. We present how we have re-designed the GEMS data-analytics framework to fully take advantage of the proposed hybrid data model. To improve analysts productivity, in addition to a C++ API for applications development, we adopt GraQL as input query language. We validate our approach implementing a set of queries on net-flow data and we compare our framework performance against Neo4j. Experimental results show significant performance improvement over Neo4j, up to several orders of magnitude when increasing the size of the input data.

Data Analytics↗