Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “storage complex”

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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Engineering a Multimission Approach to Navigation Ground Data System Operations

The Mission Design and Navigation (MDNAV) Section at the Jet Propulsion Laboratory (JPL) supports many deep space and earth orbiting missions from formulation to end of mission operations. The requirements of these missions are met with a multimission approach to MDNAV ground data system (GDS) infrastructure capable of being shared and allocated in a seamless and consistent manner across missions. The MDNAV computing infrastructure consists of compute clusters, network attached storage, mission support area facilities, and desktop hardware. The multimission architecture allows these assets, and even personnel, to be leveraged effectively across the project lifecycle and across multiple missions simultaneously. It provides a more robust and capable infrastructure to each mission than might be possible if each constructed its own. It also enables a consistent interface and environment within which teams can conduct all mission analysis and navigation functions including: trajectory design; ephemeris generation; orbit determination; maneuver design; and entry, descent, and landing analysis. The savings of these efficiencies more than offset the costs of increased complexity and other challenges that had to be addressed: configuration management, scheduling conflicts, and competition for resources. This paper examines the benefits of the multimission MDNAV ground data system infrastructure, focusing on the hardware and software architecture. The result is an efficient, robust, scalable MDNAV ground data system capable of supporting more than a dozen active missions at once.

Mission Design and Navigation (MDNAV)↗
NASA NTRS2010

Hypergolic Propellant Destruction Evaluation Cost Benefit Analysis

At space vehicle launch sites such as Vandenberg Air Force Base (VAFB), Cape Canaveral Air Force Station (CCAFS) and Kennedy Space Center (KSC), toxic vapors and hazardous liquid wastes result from the handling of commodities (hypergolic fuels and oxidizers), most notably from transfer operations where fuel and oxidizer are transferred from bulk storage tanks or transfer tankers to space launch vehicles. During commodity transfer at CCAFS and KSC, wet chemical scrubbers (typically containing four scrubbing towers) are used to neutralize fuel saturated vapors from vent systems on tanks and tanker trailers. For fuel vapors, a citric acid solution is used to scrub out most of the hydrazine. Operation of both the hypergolic fuel and oxidizer vapor scrubbers generates waste scrubber liquor. Currently, scrubber liquor from the fuel vapor scrubber is considered non-hazardous. The scrubber liquor is defined as spent citric acid scrubber solution; the solution contains complexed hydrazine I methylhydrazine and is used to neutralize nonspecification hypergolic fuel generated by CCAFS and KSC. This project is a collaborative effort between Air Force Space Command (AFSPC), Space and Missile Center (SMC), the CCAFS, and National Aeronautics and Space Administration (NASA) to evaluate microwave destruction technology for the treatment of non-specification hypergolic fuel generated at CCAFS and KSC. The project will capitalize on knowledge gained from microwave treatment work being accomplished by AFSPC and SMC at V AFB. This report focuses on the costs associated with the current non-specification hypergolic fuel neutralization process (Section 2.0) as well as the estimated costs of operating a mobile microwave unit to treat non-specification hypergolic fuel (Section 3.0), and compares the costs for each (Section 4.0).The purpose of this document is to assess the costs associated with waste hypergolic fuel. This document will report the costs associated with the current fuel neutralization process and also examine the costs of an alternative technology, microwave destruction of waste hypergolic fuel. The microwave destruction system is being designed as a mobile unit to treat non-specification hypergolic fuel at CCAFS and KSC.

Kessel, Kurt↗
DOE OSTI2025

Energy Sector Threat Brief: 2024 Round Up

What major and minor cybersecurity events affected the energy sector in the last year? What trends were observed in the events, disclosure of vulnerabilities, and other headline news? This talk will focus on real-world events put in the context of an evolving geo-political landscape. We will discuss events that had operational impact as well as events affecting third-parties with exploration of how the impact of incidents is changing as more stakeholders are involved in new projects and the complexity of the modern grid. We will focus on lessons learned from the 2024 trends that operators and their partners can apply to stay ahead of the threats in 2025.

14 - SOLAR ENERGY↗
DOE OSTI2021

Uncertainty quantification for deep learning in particle accelerator applications

With the advent of increased computational resources and improved algorithms, machine learning-based models are being increasingly applied to complex problems in particle accelerators. However, such data-driven models may provide overly confident predictions with unknown errors and uncertainties. For reliable deployment of machine learning models in high-regret and safety-critical systems such as particle accelerators, estimates of prediction uncertainty are needed along with accurate point predictions. In this investigation, we evaluate Bayesian neural networks (BNN) as an approach that can provide accurate predictions along with reliably quantified uncertainties for particle accelerator problems, and compare their performance with bootstrapped ensembles of neural networks. We select three accelerator setups for this evaluation: a storage ring, a photoinjector, and a linac. The problems span different data volumes and dimensionalities (e.g., scalar predictions as well as image outputs). It is found that BNN provide accurate predictions of the mean along with reliable estimates of predictive uncertainty across the test cases. In this vein, BNN may offer an attractive alternative to deterministic deep learning tools to generate accurate predictions with quantified uncertainties in particle accelerator applications.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Battle of the Defaults: Extracting Performance Characteristics of HDF5 under Production Load

Popular parallel I/O libraries, such as HDF5, provide tuning parameters to obtain superior performance. However, the selection of effective parameters on production systems is complex due to the interdependence of I/O software and file system layers. Hence, application developers typically use the default parameters and often experience poor I/O performance. This work conducts a benchmarking-based analysis on the HDF5 behaviors with a wide variety of I/O patterns to extract performance characteristics under the production workload. To make the analysis well controlled, we exercise I/O benchmarks on POSIX-IO, MPI-IO, and HDF5 using the same I/O patterns and in the same jobs. To address high performance variability in production environments, we repeat the benchmarks across I/O patterns, storage devices, and time intervals. Based on the results, we identified consistent HDF5 behaviors that appropriate configurations and operations on dataset layout and file-metadata placement can improve performance significantly. We apply our findings and evaluate the tuned I/O library on two supercomputers: Summit and Cori. The results show that our tuned parameters can achieve more than 10× I/O performance speedup than that with default parameters on both systems, suggesting the effectiveness, stability, and generality of our solution.

Xie, Bing↗
DOE OSTI2024

Coupling of the Electricity and Transportation Sectors - Part I: Sector Overviews

“Sector coupling” is a concept that addresses potential designs for the future power industry. Traditionally, the energy sectors, i.e., electricity supply, transport, and industry, have functioned largely independently from one another. Thus, the concept of sector coupling means that the electricity sector would become the central pillar of the energy system, supplying the other sectors – transportation and industry – with energy in various ways, a scheme described by the term “Power-to-X”. This report delves into the ambitious goal set by the United States to achieve net-zero emissions by 2050, with a pivotal milestone of making half of all passenger vehicles sold in America zero-emission by 2030. Central to achieving this objective is the electrification of the transportation sector, resulting in complex interactions between this sector and the electric industry. As electric vehicles become more prevalent, a shift in the dependency on electricity for vehicle charging emerges, alongside a reduction in the electricity demand associated with maintaining the fossil fuel supply chain. Both the electricity and fossil fuel have been identified as critical infrastructure sectors, the transportation sector's historical reliance on fossil fuels, and the mature supply chain supporting them are explored. This study emphasizes the existing sectoral coupling between the electric energy and transportation sectors, extending beyond vehicle charging to essential operations at refineries, pipeline facilities, storage, and fuel extraction. Recognizing the critical dependency of fossil fuel supply chain operations on the electric sector, this research underscores the need for a comprehensive view of the evolving dynamics between the transportation and electric sectors. This study has been split into two segments, Part-I provides an overview of the existing fossil fuel supply chain architecture and the electrical sector. We provide an in-depth analysis of the grid-transportation sectoral coupling, its interactions, the vulnerabilities and essential take-aways that would help us to address them and apply towards an electrified transportation sector in the future. We engaged with stakeholders to understand their expectations in enabling an electrified transportation. We accumulate the understandings from the current fossil fuel-based system in developing a risk matrix, by identifying all the threats and vulnerabilities and how would they apply to both the current and future transportation systems in Part-II of this report.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2021

Microgravity Science Database Development

Throughout NASA’s history, the agency has developed a plethora of complex systems, such as the International Space Station and the space shuttle, and performed research in several fields spanning the gamut from psychology to welding and materials research. Throughout these studies, an extensive amount of data has been generated and unfortunately at times regenerated. As Barend Mons states “Huge sums of taxpayer funds go to waste because such data cannot be reused.”[2] While his comments were directed at the state of data management in the European Union, it is no less valid for data management practices in the United States. The issues surrounding data management, including storage, retrieval, and analysis, will continue to be of utmost importance as the agency aims to responsibly utilize funds and gather the maximum benefit from flight and ground experiments.

Data↗
DOE OSTI2020

Molecular Structure and Electron Affinity of Metal-Solvent Complexes: Insights from Density Functional Theory Simulations

A molecular level understanding of the structure and energetics of the monovalent and divalent metal ion complexes is of great importance for development of next-generation batteries. Here, Density Functional Theory (DFT) simulations at the ωb97xD/6-31 + G(d,p) level of theory are performed to investigate the interaction of metal ions (Li + , Na + , K + , Mg 2+ , Ca 2+ , Zn 2+ ) with 26 organic solvent molecules. The reduction energetics (electron affinity and reduction potential) and structural responses of the solvent molecules and the molecular complexes are discussed. The DFT calculations are carried out to investigate the structure, energetics and electron affinities of chelated complexes of water (H 2 O), tetrahydrofuran (THF) and di-methoxy ethane (DME) solvent molecules. Additionally, ab initio dynamic simulations (AIMD) at 298 K using atom centered density matrix propagation (ADMP) formalism are performed to understand the spontaneous structure formation upon electron attachment of the metal ion-solvent complexes. The ADMP simulations indicate the decomposition of Mg + -(DME) 3 complex via cleavage of C–O bond of one of the three DME molecules indicating irreversible decomposition of DME in the presence of the Mg + radical. We believe that the data collected as part of this investigation serves as a library of fundamental knowledge towards a deeper understanding of the electrode-electrolyte interfacial reactions.

25 ENERGY STORAGE↗
DOE OSTI2023

Thermodynamic controls on the synthesis, structure and reactivity of materials for energy (Final Report)

The major objectives have been: a) to advance and use unique calorimetric capabilities to determine the energetics of oxide and other materials having possible energy applications, with an emphasis on new materials for batteries, fuel cells and solar energy conversion, b) to understand, in terms of both macroscopic energetics and microscopic structure and bonding, the interplay of defect chemistry, oxidation-reduction, and size effects at the bulk and nanoscale in determining materials properties. This project emphasizes mixed ionic-electronic conduction materials containing transition metals of variable valence, especially perovskites and lithium containing phases, with M = Mn, Fe, Co, Ni. The thermochemistry of new families of complex halide, chalcogenide, nitride and hybrid (organic-inorganic) perovskite materials were explored. The major and unique technique employed is high temperature oxide melt solution calorimetry, with careful attention given to materials synthesis and characterization. The thermochemical studies will be coupled with structural studies, especially to characterize order-disorder phenomena by in situ high temperature diffraction techniques.

14 SOLAR ENERGY↗
DOE OSTI2024

Scaling Up: Demonstrating Risk Reduction and Cost Compression for Commercial Heat Pump Water Heaters - CRADA 625 (Abstract)

Commercial heat pump water heater (CHPWH) systems significantly decarbonize the commercial and multifamily sectors by eliminating the reliance on gas-fired water heating. CHPWH systems are also well suited to include load shift controls that enable load-up and shed commands for supporting grid reliability and time-of-use pricing structure. However, they have not had wide adoption due to factors including price, complexity, and perceived risk. Although CHPWHs have been available in the US for decades, they have not made significant market gains in part because the systems have required significant and costly engineering design expertise and proved lackluster performance. Successful widespread market adoption requires a different approach; a shift from the current custom specialized expertise project design and installation to a repeatable approach that requires little specialized knowledge or expertise and can deliver persistent performance. Using this type of holistic systems approach requires effectively integrating four CHPWH system key components: primary air-to-water heat pumps; primary thermal storage tanks, a temperature maintenance system, and a control system which has capabilities to manage the primary heat pump cycles, any back-up, supplemental, or temperature maintenance heating, alarms, and grid connectivity allowing for demand response (DR), and/or load shifting. The project team has developed and will implement a suite of tools to support faster, less expensive, and more reliable field installations of CHPWH technology and with the resulting data used to further improve the tool set. These tools include: (1) A tool for optimizing system size and costs. (2) A tool that predicts annual energy use and overall system efficiency. (3) The Advanced Water Heater Specification (AWHS 8.0) defining the components of a full CHPWH system addressing performance requirements by climate zone. (4) The Qualified Products List: (QPL) of approved products that meet the specifications requirements. (5) Training materials including online on-demand modules, instructor-led training, and virtual interactive video tours of CHPWH installations in multifamily buildings. Demonstration site identification in low-income buildings in underserved communities is currently underway. Preliminarily, the team anticipates having three demonstrations in the Pacific Northwest and three in the Northeast for a total of six sites. After the demonstration sites are finalized, and M&V instrumentation installations are complete, the team will gather performance data and confirm whether the CHPWH systems perform as predicted and use the data to improve the existing tools.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Smart Preprocessing & Robust Integration Emulator

To achieve the desired particle size of biomass feedstocks during preprocessing for trouble-free handling and conversion to produce biofuels and bioproducts, the raw materials must undergo a crucial milling process. The particle size of biomass plays a critical role in subsequent biofuel manufacturing, where a larger area-to-volume ratio facilitates efficient synthesis while balancing the impact of moisture on biomass storage. To optimize biofuel production efficiency and overcome these challenges, it is imperative to accurately predict the particle size distribution (PSD) of the biomass in the design of efficient preprocessing systems. The population balance model (PBM), upon empirical calibration and validation, can provide rapid prediction of post-milling PSD of granular biomass. However, PSD has limitations related to mass conservation and the absence of moisture considerations. To overcome these drawbacks, a deep learning model called the enhanced deep neural operator (DNO+) is implemented in the code. This model not only retains the capabilities of the PBM in handling complex mapping functions but also incorporates additional factors influencing the system. By considering various experimental conditions such as sieve size and moisture content, the trained DNO+ model can effectively predict the PSD after milling for any given feed PSD. To further reduce the reliance on experimental data, the PBM is integrated into the DNO+ model, resulting in a physics-informed DNO+ (PIDNO+). The PIDNO+ model addresses the non-conservation of quality exhibited by the PBM while inheriting the advantages of the DNO+ model in considering multiple influencing factors. Moreover, the PIDNO+ model significantly reduces the amount of data required for model training. Both deep learning models, i.e., DNO+ and PIDNO+, are excellent in predictive performance, offering swift and accurate machine learning-based predictions. The use of this code that contains these models will assist in guiding the proper milling equipment selection and operational conditions to achieve the desired biomass particle sizes, ensuring the efficiency of subsequent biofuel and bioproduct production processes.

Xia, Yidong [Idaho National Laboratory (INL), Idah↗
NASA NTRS1990

Sparse distributed memory overview

The Sparse Distributed Memory (SDM) project is investigating the theory and applications of massively parallel computing architecture, called sparse distributed memory, that will support the storage and retrieval of sensory and motor patterns characteristic of autonomous systems. The immediate objectives of the project are centered in studies of the memory itself and in the use of the memory to solve problems in speech, vision, and robotics. Investigation of methods for encoding sensory data is an important part of the research. Examples of NASA missions that may benefit from this work are Space Station, planetary rovers, and solar exploration. Sparse distributed memory offers promising technology for systems that must learn through experience and be capable of adapting to new circumstances, and for operating any large complex system requiring automatic monitoring and control. Sparse distributed memory is a massively parallel architecture motivated by efforts to understand how the human brain works. Sparse distributed memory is an associative memory, able to retrieve information from cues that only partially match patterns stored in the memory. It is able to store long temporal sequences derived from the behavior of a complex system, such as progressive records of the system's sensory data and correlated records of the system's motor controls.

Raugh, Mike↗
NASA NTRS2005

Intelligent Sensors: An Integrated Systems Approach

The need for intelligent sensors as a critical component for Integrated System Health Management (ISHM) is fairly well recognized by now. Even the definition of what constitutes an intelligent sensor (or smart sensor) is well documented and stems from an intuitive desire to get the best quality measurement data that forms the basis of any complex health monitoring and/or management system. If the sensors, i.e. the elements closest to the measurand, are unreliable then the whole system works with a tremendous handicap. Hence, there has always been a desire to distribute intelligence down to the sensor level, and give it the ability to assess its own health thereby improving the confidence in the quality of the data at all times. This paper proposes the development of intelligent sensors as an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the NASA Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Intelligent Systems Health Monitoring (ISHM) vision. This paper outlines some fundamental issues in the development of intelligent sensors under the following two categories: Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS).

Mahajan, Ajay↗
NASA NTRS2013

Integrated Ground Operations Demonstration for Responsive Space Access

Integrated Ground Operations Demonstration Units (IGODU) project developed to mature, integrate and demonstrate advancements in cryogenics, system health management and command and control technologies. Two Distinct Testing Environments: a) GODU Integrated Refrigeration and Storage - GODU LH2; b) GODU Autonomous Control - GODU LO2. Scope: I. GODU LH2: a) Investigate alternative storage and distribution architecture for future cryogenic propellant operations. b) Demonstrate advanced cryogenic propellant handling operations (liquefaction, storage and distribution) of normal boiling point and sub-cooled cryogenic propellants. II. GODU L02: a) Develop and demonstrate advanced control and health management technologies and techniques to autonomously control cryogenic propellant servicing operations. b) Investigate modern COTS hardware and control systems in an effort to reduce the "standing army" of engineers associated with maintaining and operating ground systems through the use of health management and autonomous control technologies. Goals: a) Raise Technology Readiness Levels (TRL) and Integration Readiness Levels (IRL) of several key technology development areas. b) Reduce operations lifecycle costs of future test programs and launch complexes. c) Demonstrate technologies for future exploration beyond low earth orbit. d) Serve as test environments for extraterrestrial surface operations.

Johnson, Robert G.↗
DOE OSTI2020

An Overview of R and D on Retrievability and Retrieval Technology in Germany - 20462

Retrievability is a term that is included in most radioactive waste management programs around the world. Although national definitions vary, the overall understanding of retrievability concerns the ability to recover waste packages from the repository mine after their emplacement. Different countries may implement retrievability in very different ways, ranging from a built-in reversibility into the emplacement process to the stipulation that retrievability may in no way impede passive safety in the post-closure phase. Germany takes a middle course such that retrievability in a HLW repository (repository for high level radioactive waste) may have no significant detrimental effect on passive safety. In Germany, the current siting process considers rock salt, clay rock, and crystalline rock as potential host rocks. Therefore, Research and Development (R and D) has been investigating repository concepts and retrievability in all host rocks. After introduction of retrievability in 2010, existing repository concepts were modified to facilitate retrieval. The changes made comprised, for example, equipping boreholes with steel liners, developing new technologies, and modifying existing emplacement devices. Apart from retrieval of HLW, retrieval of other wastes from underground repositories that were designed and operated without retrievability in mind, poses major technical and scientific challenges. Currently, studies are under way to investigate the feasibility and costs of partial retrieval of waste from an underground repository for hazardous and highly toxic waste in France, Stocamine. With regard to retrieval, the rock-mechanical conditions are deteriorating rapidly, so time is of the essence. In the Asse II mine in Germany, about 126,500 waste casks with low and intermediate level waste await retrieval. The repository mine suffers from difficult rock-mechanical conditions and inflow of brine, locally into emplacement areas. The Federal Company for Radioactive Waste Disposal (BGE) is legally required to retrieve all wastes from the Asse. Due to the specific challenges, R and D is needed to develop technical solutions for the safe retrieval from each of the emplacement chambers. R and D on retrievability and retrieval technology does not only address challenges in radioactive or toxic waste retrieval but may also help to germinate innovation to better master complex underground situations in general, e.g. in deep mining, tunneling, or repository construction. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Southeast Regional CO 2 Utilization and Storage Acceleration Partnership (SECARB-USA): Data Quality Methodology (4.2.1)

SECARB-USA Deliverable 4.2.1 utilizes the outputs from the Needs Assessment (Subtask 2.1) to develop a data quality methodology. Many types of data are needed to evaluate a site for technical and financial viability. Several inventories of data types have been produced (for example NETL, 2010). The objective here is to organize the data types so that the needs met are specified. From this cross index (Table 1 in the Appendix), it will be possible in future tasks to (1) determine, on a site-specific basis, how much of each data type is required at each stage of a project to meet the need, and conversely (2) to further specify and define the data collection methods applied such that the data are tailored to fit that need. Derivative tables can then be developed to semi-quantitively evaluate the extent to which need is critical for early go/no decision points, or if it is more important than average, requiring faster or larger capitalization and spend to meet the need. In an additional step, the current availability of data for a site can be semi-quantitively assessed. From the table of data criticality and the table of data availability, site-specific cost for meeting the data needs can be determined, and allow a pre-permit spend estimated for a portfolio of projects. All of the data needs to evaluate a site are somewhat interconnected. We used criterion (2) above to determine if the data collection design would have to be modified to meet the need; if this was commonly true a linkage was shown. The application of this cross index to sites in the subsequent tasks will demonstrate that the demand for data types varies site-to-site and project-to-project. Examples of factors to be considered are the complexity of the geology, the injection goals such as rate and duration of the injection, and the types of risk and risk tolerance of key stakeholders. In future tasks the team will compare the demand for data with existing data availability. This will, in turn, determine when data needs to be acquired to support project development. For example, in a project area with complex structure, 3-D seismic data may be needed earlier and more urgently than in an area with simple rock body geometries. In some locations, a 3-D seismic survey has already been collected and can be purchased. In other locations the project developer will need to collect these data. For another example, a project near an urban area or near to a park may generate earlier and more substantive public concern than a site that is developed in mined lands. A calculation using the derivative from table 1 will show the different investment needs. Project cost will vary corresponding to data criticality and data availability.

42 ENGINEERING↗
DOE OSTI2024

Photoinitiated thermoset polymerization through controlled release of metathesis catalysts encapsulated in poly(phthalaldehyde)

Photoinitiated polymerization enables spatiotemporal control of reaction conditions and can thereby generate materials with high complexity while consuming minimal energy. Where ring opening metathesis polymerization (ROMP) is concerned, photo-activated processes are typically enabled by chemical inhibition of ruthenium carbenes via the careful design of complexed ligands such that photoactivation can proceed through an isomerization or ligand dissociation event. In this contribution, we have explored a new approach to photoinitiation of ROMP based on physical inhibition through microencapsulation and controlled release of metathesis catalysts. Micron-sized particles of poly(phthalaldehyde) (PPA), catalyst, and photoacid generator were fabricated by spray drying. The particles were dispersed in dicyclopentadiene monomer, after which polymerization was initiated through temperature or UV exposure, both inducing depolymerization of the PPA particles and in situ catalyst release. The monomer/particle dispersions were found to be stable and reproducibly polymerizable with 3 weeks of storage at room temperature. Furthermore, the dispersions can be used for both photo- and thermal-initiated frontal ROMP, yielding a polymerized thermoset of equivalent properties to conventional bulk- and frontally-polymerized analogues. In conclusion, this work will ultimately enable new manufacturing techniques for ROMP-based materials, due to the modular, easily tunable nature of the underlying initiating system and its unparalleled stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Semantic Property Graph for Scalable Knowledge Graph Analytics

Graphs are a natural and fundamental representation to describe entities, relationships, activities, and evolution of complex systems. Many domains such as communication, citation, procurement, biology, social media, and transportation can be modeled as a set of entities and their relationships. Resource Description Framework (RDF) and Labeled Property Graph (LPG) are two of the most used data models to encode information in a graph. Both models are similar in terms of using basic graph elements such as nodes and edges but differ in terms of the modeling approach, expressibility, serialization, and target applications. RDF is a flexible data exchange model for expressing information about entities but it tends to a have high memory footprint and inefficient storage, which does not make it a natural choice to perform scalable graph analytics. In contrast, LPG has gained traction as a reliable model to perform scalable graph analytic tasks such as sub-graph matching, network alignment, and real-time knowledge graph query. It provides efficient storage, fast traversal, and flexibility to model various real-world domains. At the same time, the LPG lacks the support of a formal knowledge representation such as an ontology to provide automated knowledge inference. We propose Semantic Property Graph (SPG) as a logical projection of reified RDF into the LPG model. SPG continues to use RDF ontology to define the type hierarchy of the projected graph and validate it against a given ontology. We present a framework to convert reified RDF graphs into SPG using two different computing environments. We also present cloud-based graph migration capabilities using Amazon Web Services.

Purohit, Sumit↗