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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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NASA NTRS2012

Model-Based Fault Diagnosis: Performing Root Cause and Impact Analyses in Real Time

Generic, object-oriented fault models, built according to causal-directed graph theory, have been integrated into an overall software architecture dedicated to monitoring and predicting the health of mission- critical systems. Processing over the generic fault models is triggered by event detection logic that is defined according to the specific functional requirements of the system and its components. Once triggered, the fault models provide an automated way for performing both upstream root cause analysis (RCA), and for predicting downstream effects or impact analysis. The methodology has been applied to integrated system health management (ISHM) implementations at NASA SSC's Rocket Engine Test Stands (RETS).

Figueroa, Jorge F.↗

NASA NTRS2012

NASA Tech Briefs, February 2012

This issue contains the following briefs: (1) Optical Comb from a Whispering Gallery Mode Resonator for Spectroscopy and Astronomy Instruments Calibration (2) Real-Time Flight Envelope Monitoring System (3) Nemesis Autonomous Test System (4) Mirror Metrology Using Nano-Probe Supports (5) Automated Lab-on-a-Chip Electrophoresis System (6) Techniques for Down-Sampling a Measured Surface Height Map for Model Validation (7) Multi-Component, Multi-Point Interferometric Rayleigh/Mie Doppler Velocimeter (8) Frequency to Voltage Converter Analog Front-End Prototype (9) Dust-Tolerant Intelligent Electrical Connection System (10) Gigabit Ethernet Asynchronous Clock Compensation FIFO (11) High-Speed, Multi-Channel Serial ADC LVDS Interface for Xilinx Virtex-5 FPGA (12) Glovebox for GeoLab Subsystem in HDU1-PEM (13) Modified Process Reduces Porosity when Soldering in Reduced Gravity Environments (14) Use of Functionalized Carbon Nanotubes for Covalent Attachment of Nanotubes to Silicon (15) Flexible Plug Repair for Shuttle Wing Leading Edge (16) Three Dimensionally Interlinked, Dense, Solid Form of Single-Walled CNT Ropes (17) Axel Robotic Platform for Crater and Extreme Terrain Exploration (18) Site Tamper and Material Plow Tool - STAMP (19) Magnetic Interface for Segmented Mirror Assembly (20) Transpiration-Cooled Spacecraft-Insulation-Repair Fasteners (21) Fluorescence-Based Sensor for Monitoring Activation of Lunar Dust (22) Aperture Ion Source (23) Virtual Ultrasound Guidance for Inexperienced Operators (24) Model-Based Fault Diagnosis: Performing Root Cause and Impact Analyses in Real Time (25) Interactive Schematic Integration Within the Propellant System Modeling Environment (26) Magnetic and Electric Field Polarizations of Oblique Magnetospheric Chorus Waves (27) Variable Sampling Mapping.

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NASA NTRS1993

Intelligent neuroprocessors for in-situ launch vehicle propulsion systems health management

Efficacy of existing on-board propulsion systems health management systems (HMS) are severely impacted by computational limitations (e.g., low sampling rates); paradigmatic limitations (e.g., low-fidelity logic/parameter redlining only, false alarms due to noisy/corrupted sensor signatures, preprogrammed diagnostics only); and telemetry bandwidth limitations on space/ground interactions. Ultra-compact/light, adaptive neural networks with massively parallel, asynchronous, fast reconfigurable and fault-tolerant information processing properties have already demonstrated significant potential for inflight diagnostic analyses and resource allocation with reduced ground dependence. In particular, they can automatically exploit correlation effects across multiple sensor streams (plume analyzer, flow meters, vibration detectors, etc.) so as to detect anomaly signatures that cannot be determined from the exploitation of single sensor. Furthermore, neural networks have already demonstrated the potential for impacting real-time fault recovery in vehicle subsystems by adaptively regulating combustion mixture/power subsystems and optimizing resource utilization under degraded conditions. A class of high-performance neuroprocessors, developed at JPL, that have demonstrated potential for next-generation HMS for a family of space transportation vehicles envisioned for the next few decades, including HLLV, NLS, and space shuttle is presented. Of fundamental interest are intelligent neuroprocessors for real-time plume analysis, optimizing combustion mixture-ratio, and feedback to hydraulic, pneumatic control systems. This class includes concurrently asynchronous reprogrammable, nonvolatile, analog neural processors with high speed, high bandwidth electronic/optical I/O interfaced, with special emphasis on NASA's unique requirements in terms of performance, reliability, ultra-high density ultra-compactness, ultra-light weight devices, radiation hardened devices, power stringency, and long life terms.

Gulati, S.↗

NASA NTRS1983

Analysis of the impact of error detection on computer performance

Conventionally, reliability analyses either assume that a fault/error is detected immediately following its occurrence, or neglect damages caused by latent errors. Though unrealistic, this assumption was imposed in order to avoid the difficulty of determining the respective probabilities that a fault induces an error and the error is then detected in a random amount of time after its occurrence. As a remedy for this problem a model is proposed to analyze the impact of error detection on computer performance under moderate assumptions. Error latency, the time interval between occurrence and the moment of detection, is used to measure the effectiveness of a detection mechanism. This model is used to: (1) predict the probability of producing an unreliable result, and (2) estimate the loss of computation due to fault and/or error.

Shin, K. C.↗

NASA NTRSDate not supplied

Fault Management Algorithm Risk Assessment for the NASA Space Launch System

This presentation describes the false positive (FP) and false negative (FN) risk assessment process currently being conducted for the Space Launch System (SLS) Artemis II Fault Management (FM) detection functions. The analysis scope, general assumptions and guide rules, and key modeling concepts were discussed to establish the basis of the risk assessments conducted. Initial analyses indicated a dominance in the total risk by software and firmware failures. This paper presents efforts applied to refine the software risks and the overall impact of implementing those modifications. Current analyses conducted on the detection functions implemented for the SLS Artemis II mission indicate primary risk drivers for the individual FM detection functions are flight software failures, firmware design failures, and hardware Common Cause Failures (CCFs). There still remains issues of how to account for time and redundancy in the software risk estimations.

probability risk analysis↗

NASA NTRSDate not supplied

Fault Management Algorithm Risk Assessment for the NASA Space Launch System

This paper presents the false positive (FP) and false negative (FN) risk assessment process currently being conducted for the Space Launch System (SLS) Artemis II Fault Management (FM) detection functions. The analysis scope, general assumptions and guide rules, and key modeling concepts were discussed to establish the basis of the risk assessments conducted. Initial analyses indicated a dominance in the total risk by software and firmware failures. This paper presents efforts applied to refine the software risks and the overall impact of implementing those modifications. Current analyses conducted on the detection functions implemented for the SLS Artemis II mission indicate primary risk drivers for the individual FM detection functions are flight software failures, firmware design failures, and hardware Common Cause Failures (CCFs). There still remains issues of how to account for time and redundancy in the software risk estimations.

probability risk analysis↗

NASA NTRS2012

Extended Testability Analysis Tool

The Extended Testability Analysis (ETA) Tool is a software application that supports fault management (FM) by performing testability analyses on the fault propagation model of a given system. Fault management includes the prevention of faults through robust design margins and quality assurance methods, or the mitigation of system failures. Fault management requires an understanding of the system design and operation, potential failure mechanisms within the system, and the propagation of those potential failures through the system. The purpose of the ETA Tool software is to process the testability analysis results from a commercial software program called TEAMS Designer in order to provide a detailed set of diagnostic assessment reports. The ETA Tool is a command-line process with several user-selectable report output options. The ETA Tool also extends the COTS testability analysis and enables variation studies with sensor sensitivity impacts on system diagnostics and component isolation using a single testability output. The ETA Tool can also provide extended analyses from a single set of testability output files. The following analysis reports are available to the user: (1) the Detectability Report provides a breakdown of how each tested failure mode was detected, (2) the Test Utilization Report identifies all the failure modes that each test detects, (3) the Failure Mode Isolation Report demonstrates the system s ability to discriminate between failure modes, (4) the Component Isolation Report demonstrates the system s ability to discriminate between failure modes relative to the components containing the failure modes, (5) the Sensor Sensor Sensitivity Analysis Report shows the diagnostic impact due to loss of sensor information, and (6) the Effect Mapping Report identifies failure modes that result in specified system-level effects.

Melcher, Kevin↗

NASA NTRS1988

Advanced Earth-to-orbit propulsion technology program overview: Impact of civil space technology initiative

The NASA Earth-to-Orbit (ETO) Propulsion Technology Program is dedicated to advancing rocket engine technologies for the development of fully reusable engine systems that will enable space transportation systems to achieve low cost, routine access to space. The program addresses technology advancements in the areas of engine life extension/prediction, performance enhancements, reduced ground operations costs, and in-flight fault tolerant engine operations. The primary objective is to acquire increased knowledge and understanding of rocket engine chemical and physical processes in order to evolve more realistic analytical simulations of engine internal environments, to derive more accurate predictions of steady and unsteady loads, and using improved structural analyses, to more accurately predict component life and performance, and finally to identify and verify more durable advanced design concepts. In addition, efforts were focused on engine diagnostic needs and advances that would allow integrated health monitoring systems to be developed for enhanced maintainability, automated servicing, inspection, and checkout, and ultimately, in-flight fault tolerant engine operations.

Stephenson, Frank W., Jr.↗

NASA NTRS1973

Application of Earth Resources Technology Satellite data to urban development and regional planning: Test site, County of Los Angeles

The author has identified the following significant results. Signigicant results have been obtained from the analyses of ERTS-1 imagery from five cycles over Test Site SR 124 by classical photointerpretation and by an interactive hybrid multispectral information extraction system (GEMS). Photointerpretation has produced over 25 overlays at 1:1,000,000 scale depicting regional relations and urban structure in terms of several hundred linear and areal features. A possible new fault lineament has been discovered on the northern slope of the Santa Monica mountains. GEMS analysis of the ERTS-1 products has provided new or improved information in the following planning data categories: urban vegetation; land cover segregation; manmade and natural impact monitoring; urban design; land suitability. ERTS-1 data analysis has allowed planners to establish trends that directly impact planning policies. For example, detectable grading and new construction sites quantitatively indicated the extent, direction, and rate of urban expansion which enable planners to forecast demand and growth patterns on a regional scale. This new source of information will not only assist current methods to be more efficient, but permits entirely new planning methodologies to be employed.

Raje, S.↗

NASA NTRSDate not supplied

Quantifying the Sensitivity of Condition Incidence Parameters in the Evidence Library

One approach to quantifying spaceflight risk at NASA makes use event driven probabilistic techniques. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is such a tool that estimates medical risk metrics via simulation and enables optimization of medical resources subject to mission constraints [1]. Previous analyses have informed medical set composition, exercise countermeasures, and water intake, where each analysis quantifies the risk associated with proposed variations in system design. As future mission profiles extend beyond Low-Earth Orbit (LEO) and lengthen in duration, understanding these risks and contributing factors is critical. MEDPRAT employs Monte Carlo sampling techniques to simulate missions and track the occurrence of medical events. These events follow fault-tree-like progressions through levels of severity and mitigation via medical treatment to many possible outcomes and these are reported throughout the mission. Making this possible, are the medical databases that contain evidence gathered by the Human Research Program (HRP). Quantifying the impact of uncertainty or variability in the input data is an important step in evaluating the credibility of modeling and simulation results. In this work, we investigate the sensitivity of medical risk metrics with respect to the condition incidence parameters within the Evidence Library (EL) [2] as the medical database input for MEDPRAT. The medical conditions, contained in the EL, are equipped with incidence rates that describe the likelihood that the condition will occur. These incidence rates reflect historical spaceflight data or when appropriate, terrestrial data. In this presentation, we will explore how uncertainty in these rates propagate to the medical risk described by MEDPRAT. These results identify the conditions and parameters with the largest contribution to medical risks.

Ian Lim↗

NASA NTRS2010

Application of Diagnostic Analysis Tools to the Ares I Thrust Vector Control System

The NASA Ares I Crew Launch Vehicle is being designed to support missions to the International Space Station (ISS), to the Moon, and beyond. The Ares I is undergoing design and development utilizing commercial-off-the-shelf tools and hardware when applicable, along with cutting edge launch technologies and state-of-the-art design and development. In support of the vehicle s design and development, the Ares Functional Fault Analysis group was tasked to develop an Ares Vehicle Diagnostic Model (AVDM) and to demonstrate the capability of that model to support failure-related analyses and design integration. One important component of the AVDM is the Upper Stage (US) Thrust Vector Control (TVC) diagnostic model-a representation of the failure space of the US TVC subsystem. This paper first presents an overview of the AVDM, its development approach, and the software used to implement the model and conduct diagnostic analysis. It then uses the US TVC diagnostic model to illustrate details of the development, implementation, analysis, and verification processes. Finally, the paper describes how the AVDM model can impact both design and ground operations, and how some of these impacts are being realized during discussions of US TVC diagnostic analyses with US TVC designers.

Maul, William A.↗

NASA NTRS2014

Characterization and Comparison of Vibration Transfer Paths in a Helicopter Gearbox and a Fixture Mounted Gearbox

Health monitoring of rotorcraft components, currently being performed by Health and Usage Monitoring Systems through analyses of vibration signatures of dynamic mechanical components, is very important for their safe and economic operation. HUMS analyze vibration signatures associated with faults and quantify them as condition indicators to predict component behavior. Vibration transfer paths are characterized by frequency response functions derived from the input/output relationship between applied force and dynamic response through a structure as a function of frequency. With an objective to investigate the differences in transfer paths, transfer path measurements were recorded under similar conditions in the left and right nose gearboxes of an AH-64 helicopter and in an isolated left nose gearbox in a test fixture at NASA Glenn Research Center. The test fixture enabled the application of measured torques-common during an actual operation. An impact hammer as well as commercial and lab piezo shakers, were used in conjunction with two types of commercially available accelerometers to collect the vibration response under various test conditions. The frequency response functions measured under comparable conditions of both systems were found to be consistent. Measurements made on the fixture indicated certain real-world installation and maintenance issues, such as sensor alignments, accelerometer locations and installation torques, had minimal effect. However, gear vibration transfer path dynamics appeared to be somewhat dependent on the presence of oil, and the transfer path dynamics were notably different if the force input was on the internal ring gear rather than on the external gearbox case.

structures↗

NASA NTRS2002

Evaluation of Standard Gear Metrics in Helicopter Flight Operation

Each false alarm made by a machine monitoring system carries a high price tag. The machine must be taken out of service, thoroughly inspected with possible disassembly, and then made ready for service. Loss of use of the machine and the efforts to inspect it are costly. In addition, if a monitoring system is prone to false alarms, the system will soon be turned off or ignored. For aircraft applications, one growing concern is that the dynamic flight environment differs from the laboratory environment where fault detection methods are developed and tested. Vibration measurements made in flight are less stationary than those made in a laboratory, or test facility, and thus a given fault detection method may produce more false alarms in flight than might be anticipated. In 1977. Stewart introduced several metrics, including FM0 and FM4, for evaluating the health of a gear. These metrics are single valued functions of the vibration signal that indicate if the signal deviates from an ideal model of the signal. FM0 is a measure of the ratio of the peak-to-peak level to the harmonic energy in the signal. FM4 is the kurtosis of the signal with the gear mesh harmonics and first order side bands removed. The underlying theory is that a vibration signal from a gear in good condition is expected to be dominated by a periodic signal at the gear mesh frequency. If one or a small number of gear teeth contain damage or faults, the signal will change, possibly showing increased amplitude, local phase changes or both near the damaged region of the gear. FM0 increases if a signal contains a local increase in amplitude. FM4 increases if a signal contains a local increase in amplitude or local phase change in a periodic signal. Over the years, other single value metrics were also introduced to detect the onset and growth of damage in gears. These various metrics have detected faults in several gear tests in experimental test rigs. Conditions in these tests have been steady state in the sense that the rpm, torque and forces on the gear have been held steady. For gears used in a dynamic environment such as that occurring in aircraft, the rpm, torque and forces on the gear are constantly changing. The authors have measured significant variation in rpm and torque in the transmissions of helicopters in controlled steady flight conditions flown by highly proficient test pilots. Statistical analyses of the data taken in flight show significant nonstationarity in the vibration measurements. These deviations from stationarity may increase false alarms in gear monitoring during aircraft flight. In the proposed paper, the authors will study vibration measurements made in flight on an AH- 1 Cobra and an OH-58C Kiowa helicopters. The primary focus will be the development of a methodology to assess the impact of nonstationarity on false alarms. Issues to be addressed include how time synchronous averages are constructed from raw data as well as how lack of stationarity effects the behavior of single value metrics. Emphasis will be placed on the occurrence of false alarms with the use of standard metrics. In order to maintain an acceptable level of false alarms in the flight environment, this study will also address the determination of appropriate threshold levels, which may need to be higher than for test rigs.

Mosher, M.↗

NASA NTRS1973

First look analyses of five cycles of ERTS-1 imagery over County of Los Angeles: Assessment of data utility for urban development and regional planning

Significant results have been obtained from the analyses of ERTS-1 imagery from five cycles over Test Site SR 124 by classical photointerpretation and by an interactive hybrid multispectral information extraction system (GEMS). The synopticity, periodicity and multispectrality of ERTS coverage, available for the first time to LA County planners, have opened up both a new dimensionality in data and offer new capability in preparation of planning inputs. Photointerpretation of ERTS images has produced over 25 overlays at 1:1,000,000 scale depicting regional relations and urban structure in terms of several hundred linear and areal features. To mention only one such result, a possible new fault lineament has been discovered on the northern slope of the Santa Monica mountains in the scene 1144-18015, composited of MSS bands 4, 5, 6,. GEMS analysis of the ERTS products has provided new or improved information in the following planning data categories: urban vegetation; land cover segregation; man-made and natural impact monitoring; urban design; and suitability. ERTS data analysis has allowed planners to establish trends that directly impact planning policies. This new source of information will not only assist current methods to be more efficient, but permits entirely new planning methodologies to be employed.

Raje, S.↗

NASA NTRS2008

Inductive System Monitors Tasks

The Inductive Monitoring System (IMS) software developed at Ames Research Center uses artificial intelligence and data mining techniques to build system-monitoring knowledge bases from archived or simulated sensor data. This information is then used to detect unusual or anomalous behavior that may indicate an impending system failure. Currently helping analyze data from systems that help fly and maintain the space shuttle and the International Space Station (ISS), the IMS has also been employed by data classes are then used to build a monitoring knowledge base. In real time, IMS performs monitoring functions: determining and displaying the degree of deviation from nominal performance. IMS trend analyses can detect conditions that may indicate a failure or required system maintenance. The development of IMS was motivated by the difficulty of producing detailed diagnostic models of some system components due to complexity or unavailability of design information. Successful applications have ranged from real-time monitoring of aircraft engine and control systems to anomaly detection in space shuttle and ISS data. IMS was used on shuttle missions STS-121, STS-115, and STS-116 to search the Wing Leading Edge Impact Detection System (WLEIDS) data for signs of possible damaging impacts during launch. It independently verified findings of the WLEIDS Mission Evaluation Room (MER) analysts and indicated additional points of interest that were subsequently investigated by the MER team. In support of the Exploration Systems Mission Directorate, IMS is being deployed as an anomaly detection tool on ISS mission control consoles in the Johnson Space Center Mission Operations Directorate. IMS has been trained to detect faults in the ISS Control Moment Gyroscope (CMG) systems. In laboratory tests, it has already detected several minor anomalies in real-time CMG data. When tested on archived data, IMS was able to detect precursors of the CMG1 failure nearly 15 hours in advance of the actual failure event. In the Aeronautics Research Mission Directorate, IMS successfully performed real-time engine health analysis. IMS was able to detect simulated failures and actual engine anomalies in an F/A-18 aircraft during the course of 25 test flights. IMS is also being used in colla

Source record↗

NASA NTRS1994

Robotic technologies of the Flight Telerobotic Servicer (FTS) including fault tolerance

The original FTS concept for Space Station Freedom (SSF) was to provide telerobotic assistance to enhance crew activity and safety and to reduce crew EVA (Extra Vehicular Activity) activity. The first flight of the FTS manipulator systems would demonstrate several candidate tasks and would verify manipulator performance parameters. These first flight tasks included unlocking a SSF Truss Joint, mating/demating a fluid coupling, contact following of a contour board, demonstrating peg-in-hole assembly, and grasping and moving a mass. Future tasks foreseen for the FTS system included ORU (Orbit Replaceable Unit) change-out, Hubble Space Telescope Servicing, Gamma Ray Observatory refueling, and several in-situ SSF servicing and maintenance tasks. Operation of the FTS was planned to evolve from teleoperation to fully autonomous execution of many tasks. This wide range of mission tasks combined with the desire to evolve toward fully autonomy forced several requirements which may seen extremely demanding to the telerobotics community. The FTS requirements appear to have been created to accommodate the open-ended evolution plan such that operational evolution would not be impeded by function limitations. A recommendation arising from the FTS program to remedy the possible impacts from such ambitious requirements is to analyze candidate robotic tasks. Based on these task analyses, operational impacts against development impacts were weighed prior to requirements definition. Many of the FTS requirements discussed in the following sections greatly influenced the development cost and schedule of the FTS manipulator. The FTS manipulator has been assembled at Martin Marietta and is currently in testing. Successful component tests indicate a manipulator which achieves unprecedented performance specifications.

Chladek, John T.↗

NASA NTRS2019

Safe and Optimal Techniques Enabling Recovery, Integrity, and Assurance

There is a trend in the aviation industry to go from federated to integrated computing systems. Combining a number of traditional stand-alone federated systems into an integrated common platform (called Integrated Modular Avionics, IMA) has the benefit of increased power efficiency, reduced support hardware, and reduced cabling. However, changing from federated to integrated has a significant impact on the system architecture and hence the process of how avionic systems are to be analyzed. Traditional approaches to safety analysis become inefficient when functional boundaries can no longer be assumed for failure independence and fault isolation. In this report, we describe a tool that we developed to accelerate the safety engineer's ability to perform safety analysis of IMA systems through modeling, as well as optimize the system engineer's ability to develop a system through architecture synthesis. This work was the result of a three-year research effort called SOTERIA (Safe and Optimal Techniques Enabling Recovery, Integrity, and Assurance). We developed a compositional modeling language that supports rapid development, modification, and evaluation of architectures. The modeling language is structured such that the end-user defines a library of components with information on component reliability, connectivity, and fault propagation logic. The system model is built by instantiating the components from the library, connecting the components, and identifying the top-level faults of interest. Our tool is compositional in that the end-user only needs to define safety aspects at the component level. The tool takes the model and automatically synthesizes both the qualitative and quantitative safety analyses. We go further by allowing users to describe system information such as components to use in an architecture and their connection compatibility and automatically synthesize an architecture that meets the top-level probability target adhering to end-user specified constraints. This capability allows users to rapidly explore a design space..

Siu, Kit Y.↗

NASA NTRSDate not supplied

Repurposing Drilling Control Diagnostics for Subsurface Edge Detection and Boundary Advisement During Planetary Drilling

Informed decision-making during lunar drilling and sampling missions will require data monitoring tools and specialized ground data systems. Accurate and updated situational awareness, with ongoing data monitoring, is critical for timely responses by to incoming science data. Traverse plans and scheduled activities may need to be flexibly changed in order to react to unexpected data or situations. Unlike (for example) Mars missions, the relative lightspeed closeness of the Moon allows for near-real-time ground processing of incoming mission and instrument data. An Apollo-class lunar regolith drill will in a sense “travel” a meter or two vertically at a given subsurface characterization site. As the drill penetrates into lunar regolith, it is likely to encounter a range of material densities, orientations, fracture toughness, and (perhaps) ice percentages. Lunar drill telemetry can provide science teams with a valuable first look into the subsurface structure, the regolith bulk properties, and constituents at each drilled site. Real-time AI-based recognition and reaction to downhole situations has been developed for automated deeper drilling on Mars and beyond. We can leverage the same knowledge bases and pattern-matching as areal-time interpreter of the subsurface, a situational awareness tool during drilling operations. We recently (Sept. 2019) demonstrated this AI drilling monitoring and analysis capability, in control of in-situ drilling and sampling operations, mounted on a KREX-2 rover in Chile’s Atacama Desert. Terrestrial automated drilling log analyses in oil exploration have used similar machine learning techniques in classifying and identifying features in drilling logs –but these typically are designed assuming a drilling fluid influencing downhole measurements and data (permeability, resistivity). Drilling models and existing AI software designed to detect and respond to drilling faults and hard materials can be repurposed, for near-real-time (ground-based) interpretation of drilling telemetry –a potentially valuable advisory tool for strata boundaries and changes in drilling parameters. On the Moon, this approach could be used to study the structure and to some extent the composition of lunar regolith vs. borehole depth, based on recognizable variations in fracture hardness, drilling energy and penetration rates while actively drilling. Since the early 2000s, a series of increasingly-capable real-time drilling telemetry interpretation and characterization software tools have been developed. These subsurface models and software tools have monitored the real-time drilling data received, and automatically identified changes in drill behavior (e.g., encountering a harder target layer, bit inclusions, drill choking due to infall downhole, and others) correlating these with subsurface structures and features. We discuss the mappings between drill borehole parameters, faults or events detected, and modeled changes in rock layer boundaries, in examples drawn from field testing at analog sites in an Arctic impact crater, Rio Tinto, and Chile’s Atacama Desert. These demonstrate how subsurface structural boundaries led to fault detections and responses by the software.

drilling advisor↗