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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Programmable pseudo-random sequence generator for use with universal lidar and its associated method of operation

A pseudo-random sequence generator for use within a universal lidar system and its corresponding method of operation. The pseudo-random sequence generator uses synchronized shift registers that are in series Binary adders are provided. The signal output of each of the shift registers is tapped and directed to the binary adders. High-speed switches are provided between the shift registers and the binary adders. The switches are programmed to connect only two of the shift registers to the binary adders for each of the pseudo-random patterns being generated. The binary adders generate an output signal that is received by the first shift register. The signal propagates through all the shift registers to the last shift register. The last shift register outputs a pseudo-random sequence.

Datta, Shubhashish↗
DOE OSTI2023

Fundamental study of gas species transport in the oxygen electrode of solid oxide fuel and electrolysis cells

A fundamental analysis of multicomponent gas transport models was performed in application to the oxygen electrodes of solid oxide cells. It is common practice to neglect the effect of pressure gradients within oxygen electrodes, even though a net molar flux at the electrolyte surface implies that a pressure gradient must exist. The influence of both Darcy velocity and Knudsen flux are considered in the context of ordinary (Fickian) diffusion, the dusty gas model, and the binary friction model. Comparisons between the models and different sets of assumptions are made via parametric studies on operating load, oxygen partial pressure, microstructural properties, and electrode thickness. Results show that the pressure gradient will have a significant impact on the oxygen concentration distribution and therefore the concentration overpotential. In electrolysis mode, pressure increases up to 1 atm are predicted, indicating that pressure at the electrode/electrolyte interface could contribute to electrode delamination. Additionally, it is found that Darcy's law is insufficient for calculating the pressure distribution without accounting for the flux due to Knudsen diffusion. Additionally, it is found that for the range of properties typical of oxygen electrodes, there is a negligibly small difference between the dusty gas model and binary friction model from a practical standpoint.

08 HYDROGEN↗
NASA NTRS2016

The Asteroid Redirect Mission (ARM): Exploration of a Former Binary NEA?

The National Aeronautics and Space Administration (NASA) is developing the Asteroid Redirect Mission (ARM) as a capability demonstration for future human exploration, including use of high-power solar electric propulsion, which allows for the efficient movement of large masses through deep space. The ARM will also demonstrate the capability to conduct proximity operations with natural space objects and crewed operations beyond the security of quick Earth return. The Asteroid Redirect Robotic Mission (ARRM), currently in formulation, will visit a large near-Earth asteroid (NEA), collect a multi-ton boulder from its surface, conduct a demonstration of a slow push planetary defense technique, and redirect the multi-ton boulder into a stable orbit around the Moon. Once returned to cislunar space in the mid-2020s, astronauts aboard an Orion spacecraft will dock with the robotic vehicle to explore the boulder and return samples to Earth. The ARM is part of NASA's plan to advance technologies, capabilities, and spaceflight experience needed for a human mission to the Martian system in the 2030s. The ARM and subsequent availability of the asteroidal material in cis-lunar space, provide significant opportunities to advance our knowledge of small bodies in the synergistic areas of science, planetary defense, and in-situ resource utilization (ISRU). The current reference target for the ARM is NEA (341843) 2008 EV5, which may have been the primary body of a former binary system (Busch et al., 2011; Tardivel et al., 2016). The ARRM will perform several close proximity operations to investigate the NEA and map its surface. A detailed investigation of this object may allow a better understanding of binary NEA physical characteristics and the possible outcomes for their evolution. An overview of the ARM robotic and crewed segments, including mission operations, and a discussion of potential opportunities for participation with the ARM will be provided in this presentation.

Abell, P. A.↗
DOE OSTI2022

A KMnO 4 -Generated Colloidal Electrolyte for Redox Mediation and Anode Protection in a Li–Air Battery

The rechargeable lithium-oxygen (Li-O 2 ) battery has the highest theoretical specific energy density of any rechargeable batteries and could transform energy storage systems if a practical device could be attained. However, among numerous challenges, which are all interconnected, are polarization due to sluggish kinetics, low cycle life, small capacity, and slow rates. Here, in this study, we report on use of KMnO 4 to generate a colloidal electrolyte made up of MnO 2 nanoparticles. The resulting electrolyte provides a redox mediator for reducing the charge potential and lithium anode protection to increase cycle life. This electrolyte in combination with a stable binary transition metal dichalcogenide alloy, Nb 0.5 Ta 0.5 S 2 , as the cathode enables the operation of a Li-O 2 battery at a current density of 1 mA center dot cm -2 and specific capacity ranging from 1000 to 10000 mA center dot h center dot g -1 (corresponding to 0.1-1 mA center dot h center dot cm -2 ) in a dry air environment with a cycle life of up to 150. This colloidal electrolyte provides a robust approach for advancing Li-air batteries.

25 ENERGY STORAGE↗
NASA NTRS1993

Classifying multispectral data by neural networks

Several energy functions for synthesizing neural networks are tested on 2-D synthetic data and on Landsat-4 Thematic Mapper data. These new energy functions, designed specifically for minimizing misclassification error, in some cases yield significant improvements in classification accuracy over the standard least mean squares energy function. In addition to operating on networks with one output unit per class, a new energy function is tested for binary encoded outputs, which result in smaller network sizes. The Thematic Mapper data (four bands were used) is classified on a single pixel basis, to provide a starting benchmark against which further improvements will be measured. Improvements are underway to make use of both subpixel and superpixel (i.e. contextual or neighborhood) information in tile processing. For single pixel classification, the best neural network result is 78.7 percent, compared with 71.7 percent for a classical nearest neighbor classifier. The 78.7 percent result also improves on several earlier neural network results on this data.

Telfer, Brian A.↗
DOE OSTI2022

Enhanced delivery of engineered Fe-Mn binary oxides in heterogeneous porous media for efficient arsenic stabilization

Heterogeneity in sediment and aquifer is universal, resulting in preferential flows of injected materials in the high permeability regions and forming flow by-passed zones in the low permeability regions during in-situ subsurface remediation. This adverse effect can considerably delay the completion of remedial operations and significantly increase the cost. Column experiments were designed and conducted to study the transport of starch- and starch-xanthan gum modified Fe-Mn binary oxide particles (SFM and SXFM) in saturated heterogeneous porous media and to reveal the particles’ arsenic (As) stabilization performance. Fine-in-Coarse (FIC) and Coarse-in-Fine (CIF) patterns of heterogeneous packings were set up in the columns. Testing results demonstrated that starch-xanthan gum dual treatment on Fe-Mn binary oxides successfully improved the particles’ migration capability in heterogeneous porous media and their distribution uniformity attributed to the profound shear thinning behavior of xanthan gum solution. The addition of xanthan gum to the system increased the viscosity and shear thinning property of SXFM suspension, making it a better candidate for delivery. Both SFM and SXFM stabilized As in heterogeneously packed sediment collected from a contaminated site, with SXFM showing better stabilization performance than SFM. The stabilization effects of SXFM were 90.7-97.0%, compared to 82.0-95.2% of SFM.

Yan, Xiulan↗
NASA NTRS1993

Binary tree eigen solver in finite element analysis

This paper presents a transputer-based binary tree eigensolver for the solution of the generalized eigenproblem in linear elastic finite element analysis. The algorithm is based on the method of recursive doubling, which parallel implementation of a number of associative operations on an arbitrary set having N elements is of the order of o(log2N), compared to (N-1) steps if implemented sequentially. The hardware used in the implementation of the binary tree consists of 32 transputers. The algorithm is written in OCCAM which is a high-level language developed with the transputers to address parallel programming constructs and to provide the communications between processors. The algorithm can be replicated to match the size of the binary tree transputer network. Parallel and sequential finite element analysis programs have been developed to solve for the set of the least-order eigenpairs using the modified subspace method. The speed-up obtained for a typical analysis problem indicates close agreement with the theoretical prediction given by the method of recursive doubling.

Akl, F. A.↗
DOE OSTI2023

BitGNN: Unlocking the Performance Potential of Binary Graph Neural Networks on GPUs

Graph Neural Networks (GNNs) have shown compelling results in many graph-based learning tasks. They are, however, time-consuming. Recent work has shown a promising direction in improving GNN speed and shrinking the size — network binarization, which binarizes network values and operations. Prior work, however, mainly focused on algorithm designs, leaving it open on how to fully materialize the performance potential. This work fills the gap by proposing techniques to best map binary GNNs and their computations to fit the nature of bit manipulations, optimizations and algorithms to maximize BSpMM kernel efficiency, and solutions to other factors influencing the end-to-end time on GPUs. Results on real-world graphs show that the proposed techniques outperform state of-the-art binary GNN implementations by 21-67× with little accuracy loss.

Chen, Jou-An↗
DOE OSTI2026

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY↗
NASA NTRS1972

Design and fabrication of the Brayton rotating unit

The Brayton rotating unit (BRU), operating on a gas bearing system, has been designed, fabricated, and demonstrated for use in a closed Brayton cycle space power conversion system. The BRU uses a binary mixture of xenon and helium (molecular weight, 83.8) as the cycle working fluid and bearing lubricating medium and was designed to produce from 2.25 to 10.5 kw sub e of 1200 Hz three-phase electrical power. The single-shaft rotating assembly operates at a design speed of 36,000 rpm and comprises a radial single-stage compressor, a four-pole Rice alternator rotor, and a radial inflow turbine. Four units, a dynamic simulator and three component research packages, were supplied to the NASA Lewis Research Center for performance testing and further development.

Davis, J. E.↗
DOE OSTI2022

A Fast and Accurate Transient Stability Assessment Method Based on Deep Learning: WECC Case Study

Transient stability is one of the critical aspects of power system stability assessment. The increasing integration of inverter-based resources and the retirement of conventional synchronous generators result in the decreasing system inertia and growing complexity of system operating conditions. Using a few selected typical operating conditions cannot guarantee system transient stability in all operating conditions, and the time-domain simulation of all operating conditions requires tremendous time and is often infeasible. This paper proposes a more efficient transient stability assessment method based on deep learning. The binary search method is used to determine the critical clearing time (CCT) in creating training databased by time-domain simulation. This method is fast and accurate with 1 ms resolution. The buses whose CCTs are lower than 200 ms are considered critical buses. Buses close to each other are grouped based on their mutual admittance matrix to reduce the search space of the critical buses. This paper also proposes the generator feature normalization based on the physical model. Case study on the reduced 240-bus WECC system model demonstrates that the proposed method can predict CCT accurately and efficiently.

critical clearing time↗
DOE OSTI2022

Improving Schrödinger Equation Implementations with Gray Code for Adiabatic Quantum Computers

We reformulate the continuous-space Schrödinger equation in terms of spin Hamiltonians. For the kinetic energy operator, the critical concept facilitating the reduction in model complexity is the idea of position encoding. A binary encoding of position produces a spin-1/2 Heisenberg-like model and yields exponential improvement in space complexity when compared to classical computing. Encoding with a binary reflected Gray code (BRGC), and a Hamming-distance-2 Gray code (H2GC) reduces the model complexity down to the 𝑋⁢𝑍 and transverse Ising model, respectively. For 𝐴 qubits BRGC yields 2 𝐴 positions and is reduced to its 2-local form with O⁡(𝐴) ancillary qubits. H2GC yields 2 𝐴/2+1 positions with O⁡(𝐴 2 ) three-local penalty terms. We also identify the bijective mapping between diagonal unitaries and the Walsh series, producing the mapping of any real potential to a series of 𝑘 -local Ising models through the fast Walsh transform. Finally, in a finite volume, we provide some numerical evidence to support the claim that the total time needed for adiabatic evolution is protected by the infrared cutoff of the system. As a result, initial state preparation from a free-field wave function to an interacting system is expected to exhibit polynomial time complexity with volume and constant scaling with respect to lattice discretization for all encodings. For H2GC, if the evolution starts with the transverse Hamiltonian due to hardware restrictions, then penalties are dynamically introduced such that the low-lying spectrum reproduces the energy levels of the Laplacian. The adiabatic evolution of the penalty Hamiltonian is therefore sensitive to the ultraviolet scale. It is expected to exhibit polynomial time complexity with lattice discretization, or exponential time complexity with respect to the number of qubits given a fixed volume.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1977

Tse computers

An ultra-high-speed computer that utilizes binary images as its basic computational entity is being developed. The basic logic components perform thousands of operations simultaneously. Technologies of the fiber optics, display, thin film, and semiconductor industries are being utilized in the building of the hardware.

Schaefer, D. H.↗
NASA NTRS2013

Memory-Efficient Onboard Rock Segmentation

Rockster-MER is an autonomous perception capability that was uploaded to the Mars Exploration Rover Opportunity in December 2009. This software provides the vision front end for a larger software system known as AEGIS (Autonomous Exploration for Gathering Increased Science), which was recently named 2011 NASA Software of the Year. As the first step in AEGIS, Rockster-MER analyzes an image captured by the rover, and detects and automatically identifies the boundary contours of rocks and regions of outcrop present in the scene. This initial segmentation step reduces the data volume from millions of pixels into hundreds (or fewer) of rock contours. Subsequent stages of AEGIS then prioritize the best rocks according to scientist- defined preferences and take high-resolution, follow-up observations. Rockster-MER has performed robustly from the outset on the Mars surface under challenging conditions. Rockster-MER is a specially adapted, embedded version of the original Rockster algorithm ("Rock Segmentation Through Edge Regrouping," (NPO- 44417) Software Tech Briefs, September 2008, p. 25). Although the new version performs the same basic task as the original code, the software has been (1) significantly upgraded to overcome the severe onboard re source limitations (CPU, memory, power, time) and (2) "bulletproofed" through code reviews and extensive testing and profiling to avoid the occurrence of faults. Because of the limited computational power of the RAD6000 flight processor on Opportunity (roughly two orders of magnitude slower than a modern workstation), the algorithm was heavily tuned to improve its speed. Several functional elements of the original algorithm were removed as a result of an extensive cost/benefit analysis conducted on a large set of archived rover images. The algorithm was also required to operate below a stringent 4MB high-water memory ceiling; hence, numerous tricks and strategies were introduced to reduce the memory footprint. Local filtering operations were re-coded to operate on horizontal data stripes across the image. Data types were reduced to smaller sizes where possible. Binary- valued intermediate results were squeezed into a more compact, one-bit-per-pixel representation through bit packing and bit manipulation macros. An estimated 16-fold reduction in memory footprint relative to the original Rockster algorithm was achieved. The resulting memory footprint is less than four times the base image size. Also, memory allocation calls were modified to draw from a static pool and consolidated to reduce memory management overhead and fragmentation. Rockster-MER has now been run onboard Opportunity numerous times as part of AEGIS with exceptional performance. Sample results are available on the AEGIS website at http://aegis.jpl.nasa.gov.

Burl, Michael C.↗
NASA NTRS2026

In-Flight Calibration of ESA Hera’s Hyperscout-H Imager

ESA’s Hera space mission is on its way to the mission target, the binary asteroid (65803) Didymos. HyperScout-H, one of the instruments onboard Hera, is a hyperspectral imager operating in the visible and near-infrared regions between 0.65 and 0.95 μm. HyperScout-H will enable a detailed assessment of the composition of both objects, Didymos and its satellite Dimorphos, the characterization of space weathering effects, and the possible presence of exogenous material on their surfaces. To monitor instrument functionality, calibration exposures are acquired regularly. This article describes the in-flight calibrations carried out for HyperScout-H during the commissioning and cruise phases. Bias and dark exposures, as well as stellar field observations, were acquired several times after launch. We update the calibration data and monitor instrument performance in the space environment. In addition, images of Earth and Moon were acquired from distances of 1.5 × 10 6 to 2.0 × 10 6 km, and Mars and its satellite were imaged during the flyby. In five images, the surface of Mars fills the entire field of view, enabling cross-validation of HyperScout-H results with those reported by other Mars missions. We characterize the detector under in-flight operational conditions. The calibration data indicate that the bias pattern is stable, the dark current remains negligible for short exposures, and the detector response is highly linear. We quantify the field-of-view alignment and geometric distortion, and evaluate the point spread function based on the stellar field observations. Stellar observations and Mars swing-by data provide updated radiometric calibration constants, suggesting that in-flight conditions have slightly modified the detector’s spectral response. In-flight calibrations are essential to ensure data quality and reliability.

Image Processing↗
DOE OSTI2022

Replicating HCCI-like autoignition behavior: What gasoline surrogate fidelity is needed?

This work seeks to characterize the fidelity needed in a gasoline surrogate with the intent to replicate the complex autoignition behavior exhibited within advanced combustion engines, and specifically Homogeneous Charge Compression Ignition (HCCI). A low-temperature gasoline combustion (LGTC) engine operating in HCCI mode and a rapid compression machine (RCM) are utilized to experimentally quantify fuel reactivity, through autoignition and preliminary heat release characteristics. Fuels considered include a research grade E10 U.S. gasoline (RD5-87), three multi-component surrogates (PACE-1, PACE-8, PACE-20), and a binary surrogate (PRF88.4). Each fuel was studied at lean/HCCI-like conditions covering a wide range of temperatures and pressures that are representative of naturally aspirated to high boost engine operation. Detailed chemical kinetic modeling is also undertaken using a recently updated gasoline surrogate kinetic model to simulate the RCM experiments and to provide chemical insight into surrogate-to-surrogate differences. The LGTC engine experiments demonstrate nearly identical reactivity between PACE-20 and RD5-87 across studied conditions, while faster phasing is seen for both PACE-1 and PACE-8 due to their stronger intermediate- and low-temperature heat release (ITHR/LTHR) at naturally aspirated and boosted conditions, respectively. The RCM experiments reveal typical low-temperature, negative temperature coefficient (NTC) and intermediate-temperature autoignition behaviors at all pressure conditions for RD5-87, which are qualitatively reproduced by all surrogates. Quantitative discrepancies in both autoignition and preliminary heat release are observed for all surrogates, while their ability to replicate RD5-87 autoignition behavior follows the order of PACE-20 > PACE-1 > PACE-8 > PRF88.4. Excellent mapping is obtained between the LGTC engine and the RCM, where the engine pressure-time trajectories can be characterized by the regimes represented by the RCM autoignition isopleths. The kinetic model performs commendably when simulating both autoignition and preliminary heat release of PACE-20, while typically overpredicting ignition delay times for PACE-1, PACE-8 and PRF88.4 at high-pressure and low-temperature/NTC conditions. Sensitivity and rate of production (ROP) analyses highlight surrogate-to-surrogate differences in the governing chemical kinetics where n-pentane initiates rapid OH branching at a faster rate and an earlier timing for PACE-20 than iso-pentane does for PACE-1 and PACE-8, making it computationally more reactive than the other surrogates. The current study highlights the need to include non-standardized properties, such as the lean/HCCI-like autoignition characteristics, in addition to ASTM properties (e.g., RON, MON) as metrics of fuel reactivity and targets to be matched when formulating high-fidelity surrogates that fully capture gasoline advanced combustion behavior such as HCCI-like autoignition.

42 ENGINEERING↗
DOE OSTI2021

Efficient loading of reduced data ensembles produced at ORNL SNS/HFIR neutron time-of-flight facilities

We present algorithmic improvements to the loading operations of certain reduced data ensembles produced from neutron scattering experiments at Oak Ridge National Laboratory (ORNL) facilities. Ensembles from multiple measurements are required to cover a wide range of the phase space of a sample material of interest. They are stored using the standard NeXus schema on individual HDF5 files. This makes it a scalability challenge, as the number of experiments stored increases in a single ensemble file. The present work follows up on our previous efforts on data management algorithms, to address identified input output (I/O) bottlenecks in Mantid, an open-source data analysis framework used across several neutron science facilities around the world. We reuse an in-memory binary-tree metadata index that resembles data access patterns, to provide a scalable search and extraction mechanism. In addition, several memory operations are refactored and optimized for the current common use cases, ranging most frequently from 10 to 180, and up to 360 separate measurement configurations. Results from this work show consistent speed ups in wall-clock time on the Mantid LoadMD routine, ranging from 19% to 23% on average, on ORNL production computing systems. The latter depends on the complexity of the targeted instrument-specific data and the system I/O and compute variability for the shared computational resources available to users of ORNL’s Spallation Neutron Source (SNS) and the High Flux Isotope Reactor (HFIR) instruments. Nevertheless, we continue to highlight the need for more research to address reduction challenges as experimental data volumes, user time and processing costs increase.

Godoy, William↗
DOE OSTI2026

Vulcan-Forge: Architecture and Design of a Multi-Modal Forensic Analysis Plugin for CALDERA

Forge and VULCAN together describe an open-architecture cybersecurity analysis ecosystem that unifies forensic artifact processing, detection engineering, and vulnerability intelligence within integrated platforms. Forge operates as a plugin for MITRE CALDERA, ingesting diverse evidence formats—including EVTX, PCAP/PCAPNG, CSV, JSON, YAML, XML, binaries, and archives—to construct a unified artifact graph enriched with severity scoring, TLP classification, and audit trails. It provides subsystems for artifact parsing, streaming structured-data visualization, NetworkMiner-based packet inspection, PE/.NET binary analysis, and LLM-assisted triage and rule generation, with outputs validated against CCCS-YARA and pySigma schemas. VULCAN complements this by serving as a cybersecurity analyst platform that integrates a Neo4j knowledge graph, Qdrant vector retrieval, SSVC-based triage, and a local LLM to deliver CVE intelligence and forensic analysis through a multi-source ingest pipeline drawing from NVD, CISA KEV, EPSS, MITRE ATT&CK, and CAPEC. Together, they bridge structured threat intelligence with automated forensic analysis and detection workflows.

97 MATHEMATICS AND COMPUTING↗