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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Polarized Light Microscopy

Polarized light microscopy (PLM) is a technique which employs the use of polarizing filters to obtain substantial optical property information about the material which is being observed. This information can be combined with other microscopy techniques to confirm or elucidate the identity of an unknown material, determine whether a particular contaminant is present (as with asbestos analysis), or to provide important information that can be used to refine a manufacturing or chemical process. PLM was the major microscopy technique in use for identification of materials for nearly a century since its introduction in 1834 by William Fox Talbot, as other techniques such as SEM (Scanning Electron Microscopy), FTIR (Fourier Transform Infrared spectroscopy), XPD (X-ray Powder Diffraction), and TEM (Transmission Electron Microscopy) had not yet been developed. Today, it is still the only technique approved by the Environmental Protection Agency (EPA) for asbestos analysis, and is often the technique first applied for identification of unknown materials. PLM uses different configurations in order to determine different material properties. With each configuration additional clues can be gathered, leading to a conclusion of material identity. With no polarizing filter, the microscope can be used just as a stereo optical microscope, and view qualities such as morphology, size, and number of phases. With a single polarizing filter (single polars), additional properties can be established, such as pleochroism, individual refractive indices, and dispersion staining. With two polarizing filters (crossed polars), even more can be deduced: isotropy vs. anisotropy, extinction angle, birefringence/degree of birefringence, sign of elongation, and anomalous polarization colors, among others. With the use of PLM many of these properties can be determined in a matter of seconds, even for those who are not highly trained. McCrone, a leader in the field of polarized light microscopy, often advised, If you cant determine a specific optical property of a particle after two minutes, move onto another configuration. Since optical properties can be seen so very quickly and easily under polarized light, it is only necessary to spend a maximum of two minutes on a technique to determine a particular property, though often only a few seconds are required.

Engineering↗
NASA NTRS2017

Brachinite-Like Clast in the Kaidun Meteorite: First Report of Primitive Achondrite Material

Kaidun is a brecciated meteorite containing many different types of meteorites. It is composed of carbonaceous, enstatite, ordinary and R chondrites with smaller amounts of basaltic achondrites, impact melt products and unknown [1, 2]. Because of the multiple components and high abundance of carbonaceous chondrites, the Kaidun parent body was probably a large C-type asteroid in order to have accumulated clasts of many unrelated asteroids, and thus Kaidun contains previously unknown materials[1]. It has been suggested that the Kaidun parent body trawled through different regions of the solar system [3], but the formation of Kaidun meteorite is still uncertain. In this abstract, we report the first discovery of a brachinite-like clast in Kaidun.

Higashi, K.↗
NASA NTRS2017

Mobile/Modular BSL-4 Facilities for Meeting Restricted Earth Return Containment Requirements

NASA robotic sample return missions designated Category V Restricted Earth Return by the NASA Planetary Protection Office require sample containment and biohazard testing in a receiving laboratory as directed by NASA Procedural Requirement (NPR) 8020.12D - ensuring the preservation and protection of Earth and the sample. Currently, NPR 8020.12D classifies Restricted Earth Return for robotic sample return missions from Mars, Europa, and Enceladus with the caveat that future proposed mission locations could be added or restrictions lifted on a case by case basis as scientific knowledge and understanding of biohazards progresses. Since the 1960s, sample containment from an unknown extraterrestrial biohazard have been related to the highest containment standards and protocols known to modern science. Today, Biosafety Level (BSL) 4 standards and protocols are used to study the most dangerous high-risk diseases and unknown biological agents on Earth. Over 30 BSL-4 facilities have been constructed worldwide with 12 residing in the United States; of theses, 8 are operational. In the last two decades, these brick and mortar facilities have cost in the hundreds of millions of dollars dependent on the facility requirements and size. Previous mission concept studies for constructing a NASA sample receiving facility with an integrated BSL-4 quarantine and biohazard testing facility have also been estimated in the hundreds of millions of dollars. As an alternative option, we have recently conducted an initial trade study for constructing a mobile and/or modular sample containment laboratory that would meet all BSL-4 and planetary protection standards and protocols at a faction of the cost. Mobile and modular BSL-2 and 3 facilities have been successfully constructed and deployed world-wide for government testing of pathogens and pharmaceutical production. Our study showed that a modular BSL-4 construction could result in approximately 90% cost reduction when compared to traditional construction methods without compromising the preservation of the sample or Earth.

Calaway, M. J.↗
NASA NTRS2016

Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation

A major focus of the commercial aviation community is discovery of unknown safety events in flight operations data. Data-driven unsupervised anomaly detection methods are better at capturing unknown safety events compared to rule-based methods which only look for known violations. However, not all statistical anomalies that are discovered by these unsupervised anomaly detection methods are operationally significant (e.g., represent a safety concern). Subject Matter Experts (SMEs) have to spend significant time reviewing these statistical anomalies individually to identify a few operationally significant ones. In this paper we propose an active learning algorithm that incorporates SME feedback in the form of rationales to build a classifier that can distinguish between uninteresting and operationally significant anomalies. Experimental evaluation on real aviation data shows that our approach improves detection of operationally significant events by as much as 75% compared to the state-of-the-art. The learnt classifier also generalizes well to additional validation data sets.

anomaly detection↗
NASA NTRS2017

Informing Rodent Behavior in Space: Gene Expression and Hyper-Emotionality Following Prenatal Stress

As space exploration pushes our boundaries further away from Earth and for longer durations, we will inevitably require the use of multi-generational studies to continue our expansion. Space is a stressful environment not only due to the deleterious effect of spaceflight on physiology, but also due to confinement, limited social interactions, inherently dangerous circumstances, and many other stresses of an unknown environment. Stress can alter the brain chemistry, and these alterations can affect behavior at all stages of development, but it is especially pronounced during the perinatal period and can have longstanding effects, even into adulthood, which manifest through augmented brain function and psychopathology. This study investigated the nexus of brain chemistry and brain function by observing behavior of adult rats whose mothers were exposed to unpredictable variable prenatal stress (UVPS) while they were in the womb. The UVPS consisted of strobe light, tube restraint, and white noise, and was administered at unpredictable times of the day and also varied in length, both of which were measures taken to prevent habituation to the stressor. The offspring rats were then allowed to reach adulthood and at 90 days were subjected to a series of behavioral tests including novel object, startle response, and an unknown intruder to quantify the adult rats stress response and anxiety. Here we report these results of the behavioral analysis and correlate adult behavioral measures with the expression of genes involved in the hypothalamic-pituitary-adrenal axis, which modulates the animals stress response. We hypothesized that hyper-expression of genes involved in the HPA axis would correlate with the observed anxiety-like behaviors associated with early stress.

Moyer, E. L.↗
NASA NTRS2017

UAV Trajectory Modeling Using Neural Networks

Large amount of small Unmanned Aerial Vehicles (sUAVs) are projected to operate in the near future. Potential sUAV applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. sUAVs are expected to operate in the uncontrolled Class G airspace, which is at or below 500 feet above ground level (AGL), where many static and dynamic constraints exist, such as ground properties and terrains, restricted areas, various winds, manned helicopters, and conflict avoidance among sUAVs. How to enable safe, efficient, and massive sUAV operations at the low altitude airspace remains a great challenge. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative works on establishing infrastructure and developing policies, requirement, and rules to enable safe and efficient sUAVs' operations. To achieve this goal, it is important to gain insights of future UTM traffic operations through simulations, where the accurate trajectory model plays an extremely important role. On the other hand, like what happens in current aviation development, trajectory modeling should also serve as the foundation for any advanced concepts and tools in UTM. Accurate models of sUAV dynamics and control systems are very important considering the requirement of the meter level precision in UTM operations. The vehicle dynamics are relatively easy to derive and model, however, vehicle control systems remain unknown as they are usually kept by manufactures as a part of intellectual properties. That brings challenges to trajectory modeling for sUAVs. How to model the vehicle's trajectories with unknown control system? This work proposes to use a neural network to model a vehicle's trajectory. The neural network is first trained to learn the vehicle's responses at numerous conditions. Once being fully trained, given current vehicle states, winds, and desired future trajectory, the neural network should be able to predict the vehicle's future states at next time step. A complete 4-D trajectory are then generated step by step using the trained neural network. Experiments in this work show that the neural network can approximate the sUAV's model and predict the trajectory accurately.

Neural Networks↗
NASA NTRS2018

Using ADOPT Algorithm and Operational Data to Discover Precursors to Aviation Adverse Events

The US National Airspace System (NAS) is making its transition to the NextGen system and assuring safety is one of the top priorities in NextGen. At present, safety is managed reactively (correct after occurrence of an unsafe event). While this strategy works for current operations, it may soon become ineffective for future airspace designs and high density operations. There is a need for proactive management of safety risks by identifying hidden and "unknown" risks and evaluating the impacts on future operations. To this end, NASA Ames has developed data mining algorithms that finds anomalies and precursors (high-risk states) to safety issues in the NAS. In this paper, we describe a recently developed algorithm called ADOPT that analyzes large volumes of data and automatically identifies precursors from real world data. Precursors help in detecting safety risks early so that the operator can mitigate the risk in time. In addition, precursors also help identify causal factors and help predict the safety incident. The ADOPT algorithm scales well to large data sets and to multidimensional time series, reduce analyst time significantly, quantify multiple safety risks giving a holistic view of safety among other benefits. This paper details the algorithm and includes several case studies to demonstrate its application to discover the "known" and "unknown" safety precursors in aviation operation.

aviation safet↗
NASA NTRS2018

Evaluation of a Thermodynamic Ice Crystal Icing Model Using Experimental Ice Accretion Data

This paper presents the evaluation of a thermodynamic ice crystal icing model, previously presented to describe the possible mechanisms of icing within the core of a turbofan jet engine. It has been proposed that there are two types of distinct ice accretions based on a surface energy balance: freeze-dominated icing and melt-dominated icing. In the former, ice accretion occurs where a freeze fraction (0 to 1) of melted ice crystals freezes on a surface, along with the existing ice of the impinging water and ice mass. This freeze-dominated icing is characterized by having strong adhesion to the surface. In the latter, icing occurs from accumulated unmelted ice on a surface, where a melt fraction (0 to 1) dictates the amount of unmelted impinged ice. This melt-dominated icing is characterized by weakly bonded surface adhesion. The experimentally observed ice growth rates suggest that only a small fraction of the impinging ice remains on the surface, implying a mass loss mechanism such as splash, runback, bounce, or erosion. This mass loss parameter must be determined in conjunction with the fraction of freezing liquid water or fraction of melting ice on an icing surface. This loss parameter, however, along with the freeze and melt fraction, are the only experimental parameters that are currently not measured directly. Using reported icing growth rates from published ice crystal icing experiments, a methodology is proposed to determine these unknown parameters. This work takes reported ice accretion data from tests conducted by the National Aeronautics and Space Administration (NASA) in 2016 and tests NASA collaborated on with the National Research Council (NRC) of Canada in 2012 that examined the fundamental physics of ice crystal icing. Those research efforts sought to generate icing conditions representative of those that occur inside a jet engine when ingesting ice crystals. This paper presents the fundamental equations of the thermodynamic model, the methodology used to determine the aforementioned unknown icing parameters, and results from model evaluation using experimental data. In addition, this paper builds on the previously proposed model by adding a transient conduction term to explain ice growth behavior at the onset of experimental tests that was observed to be different from steady-state ice growth that occurred later in the test run.With the addition of this energy term, this becomes a quasi-steady model. A key finding from this work suggests that mass loss fractions can exceed 0.90 for steady ice growth periods. In addition, due to conductive heat fluxes when using a warmer-than-freezing airfoil, lower mass loss fraction values were calculated during the initial transient period.

Ice-Crystal Ice Accretion↗
NASA NTRS2017

Online Multi-Modal Learning and Adaptive Information Trajectory Planning for Autonomous Exploration

In robotic information gathering missions, scientists are typically interested in understanding variables which require proxy measurements from specialized sensor suites to estimate. However, energy and time constraints limit how often these sensors can be used in a mission. Robots are also equipped with cheaper to use navigation sensors such as cameras. In this paper, we explore a challenging planning problem in which a robot is required to learn about a scientific variable of interest in an initially unknown environment by planning informative paths and deciding when and where to use its sensors. To tackle this we present two innovations: a Bayesian generative model framework to automatically learn correlations between expensive science sensors and cheaper to use navigation sensors online, and a sampling based approach to plan for multiple sensors while handling long horizons and budget constraints. Our approach does not grow in complexity with data and is anytime making it highly applicable to field robotics. We tested our approach extensively in simulation and validated it with real data collected during the 2014 Mojave Volatiles Prospector Mission. Our planning algorithm performs statistically significantly better than myopic approaches and at least as well as a coverage-based algorithm in an initially unknown environment while having added advantages of being able to exploit prior knowledge and handle other intricacies of the real world without further algorithmic modifications.

learning↗
NASA NTRS2019

The Acquisition, Containment, and Curation of Mars Samples on Earth

The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center (henceforth AACO) is responsible for receiving and curating all of NASA’s extraterrestrial samples, current and future (as per NASA Policy Directive (NPD) 7100.10E “Curation of Extraterrestrial Materials”). As such, the AACO coordinates sample capture, containment, and transportation to the curation facility as well as documents, preserves, prepares, and distributes all of the samples within NASA’s astromaterial collections for research, education, and public outreach. Since the lunar rock and soil samples returned during the Apollo Program, NASA’s first Class V Restricted Earth Return Missions, the AACO curates six other astromaterials collections. Lessons learned from each collection and respective missions (e.g. Apollo, Genesis, Stardust) as well as advancements in science and technology have informed the AACO’s plan for acquiring and curating Martian samples. Given the nature of the collection, a mobile and modular facility is recommended. The two broad requirements a Mars sample facility must maintain are: 1) the ability to contain the samples to protect the public from exposure of an “unknown unknown” biological agent and 2) ensure the scientific integrity of the samples are maintained (while maximizing scientific outcome). Although Apollo samples were eventually deemed safe and released to the scientific community for evaluation, there is no guarantee that this will be the case for Martian samples. Therefore, the facility in which the samples will be contained and investigated must be modular and able to accommodate an array of instrumentation that could be highly variable depending on the initial scientific outcomes. Furthermore, in order to facilitate proper sample capture and containment upon landing as well as sample distribution to other laboratories with proper containment, a mobile facility is a valuable investment.

Harrington, Andrea D.↗
NASA NTRS2016

Introducing a Degree of Freedom in the Family of Generalized Logarithmic Spirals

The versatility of the family of generalized logarithmic spirals is improved by introducing a degree of freedom in the solution. The low-thrust acceleration profile now includes a control term that affects both the magnitude and the direction of the thrust. Exact and fully analytic solutions to the trajectory, the velocity, the time of flight, etc. are made available. Two integrals of motion are preserved. The first one is a generalization of the equation of the energy and depends on the values of the control parameter. The second one relates to the equation of the angular momentum. The problem of finding spiral transfers between two arbitrary state vectors reduces to solving one algebraic equation with one unknown. The degree of freedom allows fixing the time of flight of the transfer. If the time of flight is fixed, then there are two equations with two unknowns. No other iterative procedures are required. Coast arcs can be introduced in the solution naturally. An explicit expression for the maximum acceleration reached along the transfer is provided. Thanks to the symmetry properties of the solution a simple algorithm for generating periodic orbits is presented. An arbitrary number of intermediate nodes can be introduced to improve the flexibility of the solution when facing optimization problems. An example of a low-thrust gravity-assist Earth-Mars-Ceres trajectory shows that the solution is comparable to that obtained with other preliminary design techniques.

Roa, Javier↗
NASA NTRS2019

Numerical Investigation of Roughness Effects on Transition on Spherical Capsules

To address the hitherto unknown mechanism of boundary-layer transition on blunt reentry capsules, the role of roughness-induced disturbance growth on a spherical-section forebody is assessed via optimal transient growth theory and direct numerical simulations (DNS). Optimal transient-growth studies have been performed for the blunt capsule experiments at Mach 5.9 in the Hypersonic Ludwieg tube at the Technische Universität Braunschweig (HLB), which included measurements behind a patch of controlled, distributed micron-sized surface roughness. Transient-growth results for the HLB capsule indicate similar trends as the corresponding numerical data for a Mach 6 experiment in the Actively Controlled Expansion (ACE) facility of the Texas A&M University (TAMU) at a lower Reynolds number. Both configurations indicate a similar dependence on surface temperature ratio and, more important, rather low values of maximum energy gain. DNS are performed for the conditions of the HLB experiment to understand the generation of stationary disturbances by the roughness patch and the accompanying evolution of unsteady perturbations. However, no evidence of either modal or nonmodal disturbance growth in the wake of the roughness patch is found in the DNS data; thus, the physical mechanism underlying the observed onset of transition still remains unknown.

Stefan Hein↗
NASA NTRS2020

An Experimental Approach to a Rapid Propulsion and Aeronautics Concepts Testbed

Modern aircraft design tools have limitations for predicting complex propulsion-airframe interactions. The demand for new tools and methods addressing these limitations is high based on the many recent Distributed Electric Propulsion (DEP) Vertical Take-Off and Landing (VTOL) concepts being developed for Urban Air Mobility (UAM) markets. We propose that low cost electronics and additive manufacturing can support the conceptual design of advanced autonomy-enabled concepts, by facilitating rapid prototyping for experimentally driven design cycles. This approach has the potential to reduce complex aircraft concept development costs, minimize unique risks associated with the conceptual design, and shorten development schedule by enabling the determination of many "unknown unknowns" earlier in the design process and providing verification of the results from aircraft design tools. A modular testbed was designed and built to evaluate this rapid design-build-test approach and to support aeronautics and autonomy research targeting UAM applications utilizing a complex, transitioning-VTOL aircraft configuration. The testbed is a modular wind tunnel and flight model. The testbed airframe is approximately 80% printed, with labor required for assembly. This paper describes the design process, fabrication process, ground testing, and initial wind tunnel structural and thermal loading of a proof-of-concept aircraft, the Langley Aerodrome 8 (LA-8).

McSwain, Robert G.↗
NASA NTRS2020

Autonomous Assessment and Predictive Capabilities for Low-Altitude Urban Flight Operations

The integration of unmanned aerial vehicles in the national airspace will introduce new vehicle types, technologies, and operational paradigms for which safety must be maintained and hazards mitigated. One approach is to attempt to design for possible hazards and unsafe incidents that can occur at different phases of flight (pre-flight, in-flight, and post-flight) and during ground operations. Another is to mitigate safety incidents by implementing changes to policies, procedures, regulations, and design to cover personnel, equipment, and aircraft during operations. These and other techniques, not described herein, are typically conservative or adhoc in that they reduce the likelihood of risk after safety incidents have occurred. In this work, the goal is to develop a more predictive capability to monitor and mitigate risk and hazards to safety “in-time” enough for decisions to be made. In line with NASA’s Aeronautics Mission Directorate Strategic Thrust 5 [1] (In-Time System-Wide Safety Assurance), the System-Wide Safety (SWS) project under which this work falls, is developing and demonstrating innovative and safety-oriented solutions that enable modernization and aviation transformation. To that effect, this work will detail data-driven efforts on the SWS project to develop a number of safety-critical services for in-time monitoring and mitigation of hazards to low-altitude flight operations. First, hazards to these operations are identified based on previous work by NASA [2,3] and others in the aerospace industry. These hazards include (i) unsafe proximity to other vehicles, property, and people on the ground, (ii) critical system failures such as communication signal/GPS loss, unexpected propulsion system degradation, engine/power failure, and (iii) operational/environmental issues such as severe weather and gusty winds. For these hazards, safety metrics, which can be quantified and assessed are defined, models to monitor and predict them are developed, and flight test data is generated to develop, validate, and test these models, considering the complex interplay of the different hazards that define them [4-6]. In addition, the uncertainty in the non-deterministic effects that cannot be modeled nor predicted and unknown unknowns that arise after design/testing and during operations must be handled in rigorous manner. As a result, for each of the developed safety metrics, their dependencies on one another are characterized and a framework for handling the uncertainties inherent in the modeling, algorithms, and measurements required for prediction is also developed [7]. To that effect, this presentation will describe the safety metrics and services already developed and underway under the System-Wide Safety project that utilize data-driven techniques for the identification of anomalies, precursors, and trends (APTs) to monitor and mitigate hazards to safety, in-time, for urban flight operations in low-altitude airspace.

Okolo, Wendy A.↗
NASA NTRS2019

Verification of Unstructured Grid Adaptation Components

Adaptive unstructured grid techniques have made limited impact on production analysis workflows where the control of discretization error is critical to obtaining reliable simulation results. Recent progress has matured a number of independent implementations of flow solvers, error estimation methods, and anisotropic grid adaptation mechanics. Known differences and previously unknown differences in grid adaptation components and their integrated processes are identified here for study. Unstructured grid adaptation tools are verified using analytic functions and the Code Comparison Principle. Three analytic functions with different smoothness properties are adapted to show the impact of smoothness on implementation differences. A scalar advection-diffusion problem with an analytic solution that models a boundary layer is adapted to test individual grid adaptation components. Laminar flow over a delta wing and turbulent flow over an ONERA M6 wing are verified with multiple, independent grid adaptation procedures to show consistent convergence to fine-grid forces and a moment. The scalar problems illustrate known differences in a grid adaptation component implementation and a previously unknown interaction between components. The wing adaptation cases in the current study document a clear improvement to existing grid adaptation procedures. The stage is set for the infusion of verified grid adaptation into production fluid flow simulations.

Park, Michael A.↗
NASA NTRS2019

Challenges in Vehicle Safety and Occupant Protection for Autonomous Electric Vertical Take-Off and Landing (eVTOL) Vehicles

The burgeoning electric Vertical Take-off and Landing (eVTOL) vehicle industry has generated a significant level of enthusiasm amongst aviation designers, manufacturers and researchers. This industry is determined to change the urban transportation paradigm from traditional ground-based vehicles (cars, taxis, buses) to air-based eVTOL vehicles which can be summoned, much like how conventional taxi services work currently. These new eVTOL vehicles are designed to be small and lightweight and operate autonomously without user intervention. There are many unknowns as to how the industry will mature. The logistics of creating a completely new category of vehicle along with its own set of rules are complex, and there are many known - and unknown - barriers to overcome. Some (of many) known barriers include airspace management, ground logistics, physical space, and, the vehicle design itself. There are many eVTOL vehicle manufacturers and organizations working these problems presently. This report will focus on one major barrier: the level of safety as it pertains to the framework of eVTOL vehicles. A high level of safety is necessary for the vehicles to gain acceptance as the public adapts to these autonomous ride-sharing services. An overview of current levels of transportation safety and some extrapolation into how eVTOL vehicles might compare is first presented. Next, a discussion categorizing the major differences between Crash Prevention and Crash Mitigation as it pertains to eVTOL vehicle safety is included with identification of current deficiencies. The report then expands into a framework for specific ideas that could use Crash Mitigation to improve vehicle safety through a crashworthy systems level approach with several designs highlighted. Finally, a brief discussion into the regulatory approach and potential guidelines as they pertain to new eVTOL vehicles is presented. Accordingly, much of the supplemental data will be taken from sources pertaining to either General Aviation (GA) aircraft, rotorcraft, or transport category aircraft, due to the lack of overarching data from eVTOL vehicles. As of this writing, the European Aviation Safety Agency has released a draft version of a VTOL Special Condition, with a comment period closing in late 2018. It is assumed that eventual expected operations and anticipated future regulations for VTOL vehicles will consist of some combination of these (and other) sources.

Littell, Justin D.↗
NASA NTRS2019

Verification of Unstructured Grid Adaptation Components

Adaptive unstructured grid techniques have made limited impact on production analysis workflows where the control of discretization error is critical to obtaining reliable simulation results. Recent progress has matured a number of independent implementations of flow solvers, error estimation methods, and anisotropic grid adaptation mechanics. Known differences and previously unknown differences in grid adaptation components and their integrated processes are identified here for study. Unstructured grid adaptation tools are verified using analytic functions and the Code Comparison Principle. Three analytic functions with different smoothness properties are adapted to show the impact of smoothness on implementation differences. A scalar advection-diffusion problem with an analytic solution that models a boundary layer is adapted to test individual grid adaptation components. The scalar problems illustrate known differences in a grid adaptation component implementation and a previously unknown interaction between components. Laminar flow over a delta wing is verified with multiple, independent grid adaptation procedures to show consistent convergence to fine-grid forces and pitching moment.

Park, Michael A.↗
NASA NTRS2020

Chrono-Validation of Near-Real-Time Landslide Susceptibility Models via Plugin Statistical Simulations

The idea behind any validation scheme in landslide susceptibility studies is to test whether a model calibrated on a certain data can predict an unknown dataset of the same nature (landslide presences/absences and covariates). Almost the entirety of landslide susceptibility studies are validated by subsetting a single dataset into a training and test sets. This dataset usually corresponds either to event-specific or to historical inventories. Very rarely, a multi-temporal inventory is available and, in the few cases where this condition is met, the validation practices involve training a model on a specific landslide inventory, deriving a single predictive equation and validating it on a subsequent landslide inventory. This commonly leads landslide predictive studies, even those with a strong statistical rigor, to neglect the uncertainty estimation in their modeling scheme. In statistics, validation can also be performed via statistical simulations. This means that after fitting a given model, one can generate any number of predictive functions and test their predictive skills on any type and number of unknown datasets. In this work, we take a similar direction and we apply it to model and validate three separate co-seismic inventories, including an uncertainty estimation phase. We mapped these inventories within the same area in Indonesia, for three earthquakes occurred in 2012, 2017 and 2018. Specifically, we build three event-specific Bayesian Generalize Additive Models of the binomial family. From each model we then simulate 1000 predictive realizations over the remaining two inventories, by using a plug-in scheme where all the morphometric covariates are kept fixed and only the ground motion is replaced according to the prediction target. By doing so, we introduce a new analytical tool for near-real-time landslide predictive purposes, which is able to produce a probabilistic model which stands in between the definitions of susceptibility and hazard. In fact, our model is able to accurately estimate “where” and “when” - although not “how frequently” - landslide have occurred by featuring the multitemporal information of the trigger. In our findings, the simulations are quite similar to the fitted models; and the nine combinations we analyse produce excellent performance. This result confirms the assumption that “the past is the key to the future”, as we show that the relative contribution of each variable and their interactions in each probabilistic model remains practically the same across temporal replicates. This information is not trivial because it supports the routines implemented in global near-real-time applications.

Temporal validation↗