Vit Tall Oscillation Detection and Classification Software User Interface (UI)

The Vit Tall Oscillation Detection and Classification Software (ODCS) UI and underlying capabilities were designed based upon years of visualization and coding experience, having conferred with subject matter experts in the field, and having collaborated with a myriad of practitioners. In a systematic technical innovation progression fashion, the various features/modules of the software exited various Technology Readiness Level (TRL) stages in accordance with the relevant exit criterion: (1) Exit TRL 1 - peer-reviewed venues, (2) Exit TRL 2 - memorialized affirmations for the involved Concept of Operations (CONOPS), (3) Exit TRL 3 - results agreed with the posits of the parameters, (4) Exit TRL 4 - documented performance in a relevant environment, (5) Exit TRL 5 - prototype implementation developed, and (6) Exit TRL 6 - prototype implementation demonstrated on a full-scale realistic problem. A snapshot of the current version of the Vit Tall ODCS UI is shown in Figure 1.

Vit Tall ODCS Operational Viewpoint (OV)

The Vit Tall ODCS OV is predicated upon instilling a pragmatic and robust power oscillation and system instability ontology (Figure 2), utilizing an Adaptive Weighting Schema (AWS) (Figure 3), and arriving at an effective Oscillation Detection and Classification System (ODCS) (Figure 4). Collectively, Figures 2 through 4 present a logical progression of: (1) a Power Oscillation and System Instability Ontology, (2) a Power Oscillation and System Instability AWS, and (3) an ODCS approach vector.

Logical Progression from Power Oscillation and System Instability Ontology to a Power Oscillation and System Instability AWS to an ODCS

Vit Tall ODCS Concept of Operations (CONOPS)

By way of background information, The Vit Tall ODCS CONOPS is predicated upon correlating the characteristics and events between the power oscillation vantage point (Figure 5) and the system instability vantage point (Figure 6). AI-facilitation is utilized for the ensuing node correlations among the involved power oscillation and system instability elements (Figure 7). Collectively, Figures 5 through 7 present a logical progression of: (1) Power Oscillation, (2) System Instability, and (3) Node Correlations for Oscillation and Instability.

Logical Progression from Power Oscillation to System Instability to Node Correlations for Oscillation and Instability

Vit Tall Critical Infrastructure Network Analysis Software User Interface (UI)

The Vit Tall Critical Infrastructure Network Analysis Software (CINAS) UI and underlying capabilities were designed based upon years of generating decision-making-focused work product deliverables for various organizations (e.g., industry, academia, and government). The previously described node correlations for oscillation and instability within an ODCS pave the way for even more robust network analysis, via CINAS, which has the ability to incorporate upstream, downstream, and lateral data. A snapshot of a prior version of the Vit Tall CINAS UI is shown in Figure 8. Since that time, various CINAS versions have evolved to incorporate AI-based hybridized container orchestration systems with specialized secure sidecars and a focus on a global-scale scheduler, support for multi-region configurations, and a robust mechanism for removing single points of failure so as to enhance resiliency.

Vit Tall CINAS Operational Viewpoint (OV)

The Vit Tall CINAS OV is predicated upon instilling a logical and robust pathway starting with a dynamic nodal Constrained Form Analytics (CFA) graph (Figure 9), putting forth an initial Confidence Linkage (CL) posit (Figure 10), progressing through machine-generated non-coded linkages (e.g., Figures 11 through 13), determining a human-machine-generated classification/coding system as well as progressing through AI-generated coded linkages (e.g., Figures 14 through 16), settling upon a weighted build pre-transposition paradigm with various Nodes of Interest (NOI), and arriving at a post-transposition paradigm with NOI. Collectively, Figures 9 through 20 present a logical progression of: (1) Dynamic Nodal CFA, (2) Dynamic Nodal CFA with an initial CL posit, (3) Dynamic Nodal CFA with Non-Coded CL3, (4) Dynamic Nodal CFA with Non-Coded CL3 + CL2, (5) Dynamic Nodal CFA with Non-Coded CL3 + CL2 + CL1, (6) Dynamic Nodal CFA with Build of Coded CL3, (7) Dynamic Nodal CFA with Build of Coded CL2, (8) Dynamic Nodal CFA with Build of Coded CL3 + CL2, (9) Dynamic Nodal CFA with Weighted Build Snapshot Pre-Transposition with NOI, (10) Dynamic Nodal CFA with Weighted Build Snapshot Post-Transposition with NOI, (11) Dynamic Nodal CFA with Weighted Build Live Post-Transposition with NOI, and (12) Dynamic Nodal CFA with Dynamic Adaptive Weighting Build Live Post-Transposition with NOI.

Logical Progression from a Dynamic Nodal Constrained Form Analytics (CFA) to a Dynamic Nodal CFA with Dynamic Adaptive Weighting Build Live Post-Transposition with NOI

Vit Tall CINAS Concept of Operations (CONOPS)

By way of background information, the Vit Tall CINAS CONOPS is predicated upon Anomaly Detection and Isolation (ADI) of potential Components of Interest (COI) (Figure 21), which is a decreasing of the aperture from NOI to COI and progressing to a CINAS-based ADI of a winnowed set of potential COI (Figure 22), a further winnowed set (Figure 23), and a yet further winnowed set (Figure 24) using higher resolution data and/or telemetry data from lateral sensors. Collectively, Figures 21 through 24 present a logical progression of: (1) CINAS-based ADI of Potential COI, (2) CINAS-based ADI of a Winnowed Set of Potential COI, (3) CINAS-based ADI of a further Winnowed Set of Potential COI, and (4) CINAS-based ADI of a yet further Winnowed Set of Potential COI using Higher Resolution Data and/or Telemetry Data from Lateral Sensors.

Logical Progression from a CINAS-based ADI of Potential COI to a CINAS-based ADI of a yet further Winnowed Set of Potential COI using Higher Resolution Data and/or Telemetry Data from Lateral Sensors

Our Vit Tall Software Suite of Tools is a Highly Effective Amalgam