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At least 73 records · Page 4

Supporting Crew Autonomy in Deep Space Exploration: Preliminary Onboard Capability Requirements and Proposed Research Questions. Technical Report of the Autonomous Crew Operations Technical Interchange Meeting

Communication delays are a critical challenge posed by long duration deep space exploration. Space missions historically have relied on an ever-present Mission Control Center (MCC) to direct operations in near real-time. As unanticipated anomalies that defeat fault detection and resolution systems do arise, the lack of real-time communication will significantly weaken what the MCC support represents: a reliable safety net for the flight crew through its deep and diverse areas of expertise and investigative resources. As a consequence, future space vehicles and habitats need to be equipped with capabilities to support the flight crew to operate with little or no ground support. Considerations must be given to vehicle and mission designs that will fortify the traditionally ground-centered safety net and forge new support systems, when communication delays exist. In August 2018, NASA’s Human Research Program, through its Human Factors and Behavioral Performance Element, convened a Technical Interchange Meeting (TIM) on Autonomous Crew Operations at NASA Ames Research Center. The goal of the meeting was to gather input from NASA centers, industry, academia, and branches of the Department of Defense (DoD) to address how intelligent technologies can be applied to augment onboard capabilities to support crew anomaly response. The TIM featured 24 presentations by 29 speakers and hosted a total of 59 attendees, including 43 from 5 NASA centers (Ames, Johnson, Langley, Marshall, and Jet Propulsion Lab) and 4 from the DoD (3 from Army Research Lab and 1 from Naval Postgraduate School), with remaining attendees from academia (e.g., UC Davis, CMU) and industry (e.g., IBM, Siemens). Discussions were centered around three themes: standards and guidelines, lessons learned in analog environments, and technologies. To help provide a framework for discussion, a concept matrix describing anomaly response processes was created prior to the TIM (Figure 1, page 6). The matrix captures the steps involved (monitoring and detection, diagnosis, solution development and evaluation, solution implementation and verification, resolution documentation) as well as the resources and capabilities required to support these steps (data, knowledge, analysis, synthesis, resource management). A wallpaper size printout of the matrix was utilized at the TIM to solicit attendee inputs along the three themes; the activity garnered 108 submissions of ideas. Overall, what emerged from TIM discussions was a picture of mismatch between crew anomaly response needs and support that can be provided by existing intelligent technologies. The needs are broad, spanning multiple steps and processes/resources, with many of which lacking support from existing technologies, such as knowledge management throughout the steps of problem solving (especially in resolution documentation) and manpower management. The solutions provided by existing intelligent technologies are specific to the steps/processes that they are designed to support and constrained to solving only problems similar to those that have occurred before. What is lacking from technologies is typically made up by humans, specifically their complex critical thinking, creative problem solving, and domain expertise. In the end, the TIM highlighted the pressing need to support responses to onboard anomalies during autonomous crew operations, particularly those that have eluded the system tests, inspection, and other assurance processes. Such anomalies can potentially threaten crew and vehicle safety, as well as significantly impact overall operations with additional workload. These fairly rare events are difficult to anticipate and prepare for, given the state-of-the-art in intelligent technologies. This is true even for anomalies that stem from “unknown knowns”—cases in which there is sufficient external information to characterize the problem but the overall pattern fails to be recognized by the problem solver, or in which the internal knowledge needed to solve a problem is held tacitly and potentially accessible by the problem solver but not articulated. It follows that the ability to tackle anomalies lies not only with the availability of relevant information and knowledge but also their accessibility in times of need. To that end, we propose research questions along the following three broad themes: • How intelligent technologies can help make relevant knowledge and information available? • How intelligent technologies can help make relevant knowledge and information accessible? • How intelligent technologies can help support the crew operating as a team in anomaly response processes?

autonomous crew operations↗

Machine-Learned Committor Functions for Reactive Molecular Dynamics

Reactive molecular dynamics (MD) is a powerful tool for atomistic-scale modeling of a diverse range of chemical processes. However, scaling these simulations to large systems and long times scales remains a challenge because of the complexity of the potential energy function required. The authors previously developed a heuristic approach, called REACTER, that incorporates reactivity in MD simulations in a less general but much more computationally efficient manner. REACTER uses standard, fixed valence force fields as the underlying potentialenergy surface for describing all interatomic interactions but adds a procedure for enforcing user-defined reactions that occur when certain geometric constraints on relative atomic positions are satisfied. Further, these bonding changes can be accepted or rejected with a probability related tothe local thermal energy. This work seeks to generalize this approach by replacing the set of user defined geometric constraints and energetic criteria with a committor function that specifies the probability of a reaction occurring on the basis of the local atomic configuration. The committor function is a useful mathematical tool for modeling rare events but, unfortunately, is very difficult to compute for realistic systems in a general way. This work describes a method for approximating the committor function using a machine learning approach, specifically a deep neural network trained with data from reactive MD and DFT-based dynamics simulations. This network is coupled to the existing REACTER protocol, as implemented in the LAMMPS MD package, and used to make on-the-fly predictions of reaction probabilities without the more extensive user input previously required. The new method is demonstrated using the polymerization of polystyrene as a case study. Although very dependent on the quality and quantity of training data, machine-learned committor functions show promise as a method for incorporating reaction probability from higher level calculations into highly scalable MD simulations.

polymer simulations↗

Bayesian Estimation of Earth’s Undiscovered Mineralogical Diversity Using Noninformative Priors

Recently, statistical distributions have been explored to provide estimates of the mineralogical diversity of Earth, and Earth-like planets. In this paper, a Bayesian approach is introduced to estimate Earth’s undiscovered mineralogical diversity. Samples are generated from a posterior distribution of the model parameters using Markov chain Monte Carlo simulations such that estimates and inference are directly obtained. It was previously shown that the mineral species frequency distribution conforms to a generalized inverse Gauss–Poisson (GIGP) large number of rare events model. Even though the model fit was good, the population size estimate obtained by using this model was found to be unreasonably low by mineralogists. In this paper, several zero-truncated, mixed Poisson distributions are fitted and compared, where the Poisson-lognormal distribution is found to provide the best fit. Subsequently, the population size estimates obtained by Bayesian methods are compared to the empirical Bayes estimates. Species accumulation curves are constructed and employed to estimate the population size as a function of sampling size. Finally, the relative abundances, and hence the occurrence probabilities of species in a random sample, are calculated numerically for all mineral species in Earth’s crust using the Poisson-lognormal distribution. These calculations are connected and compared to the calculations obtained in a previous paper using the GIGP model for which mineralogical criteria of an Earth-like planet were given.

Bayesian statistics↗

Infusing Statistical Thinking into the NASA Quesst Community Test Campaign

Statistical thinking permeates many important decisions as NASA plans its Quesst mission, which will culminate in a series of community overflights using the X-59 aircraft to demonstrate low-noise supersonic flight. Month-long longitudinal surveys will be deployed to assess human perception and annoyance to this new acoustic phenomenon. NASA works with a large contractor team to develop systems and methodologies to estimate noise doses, to test and field socio-acoustic surveys, and to study the relationship between the two quantities, dose and response, through appropriate choices of statistical models. This latter dose-response relationship will serve as an important tool as national and international noise regulators debate whether overland supersonic flights could be permitted once again within permissible noise limits. In this presentation we highlight several areas where statistical thinking has come into play, including issues of sampling, classification and data fusion, and analysis of longitudinal survey data that are subject to rare events and the consequences of measurement error. We note several operational constraints that shape the appeal or feasibility of some decisions on statistical approaches, and we identify several important remaining questions to be addressed.

Bayesian model↗

The Containment Assurance Risk Framework of the Mars Sample Return Program

The Mars Sample Return campaign aims at bringing rock and atmospheric samples from Mars to Earth through a series of robotic missions. These missions would collect the samples being cached and deposited on Martian soil by the Perseverance rover, place them in a container, and launch them into Martian orbit for subsequent capture by an orbiter that would bring them back. Given there exists a non-zero probability that the samples contain biological material, precautions are being taken to design systems that would break the chain of contact between Mars and Earth. These include techniques such as sterilization of Martian particles, redundant containment vessels, and a robust reentry capsule capable of accurate landings without a parachute. Requirements exist that the probability of containment not assured of Martian-contaminated material into Earth’s biosphere be less than one in a million. To demonstrate compliance with this strict requirement, a statistical framework was developed to assess the likelihood of containment loss during each sample return phase and make a statement about the total combined mission probability of containment not assured. The work presented here describes this framework, which considers failure modes or fault conditions that can initiate failure sequences ultimately leading to containment not assured. Reliability estimates are generated from databases, design heritage, component specifications, or expert opinion in the form of probability density functions or point estimates and provided as inputs to the mathematical models that simulate the different failure sequences. The probabilistic outputs are then combined following the logic of several fault trees to compute the ultimate probability of containment not assured. Given the multidisciplinary nature of the problem and the different types of mathematical models used, the statistical tools needed for analysis are required to be computationally efficient. While standard Monte Carlo approaches are used for fast models, a multi-fidelity approach to rare event probabilities is proposed for expensive models. In this paradigm, inexpensive low-fidelity models are developed for computational acceleration purposes while the expensive high-fidelity model is kept in the loop to retain accuracy in the results. This work presents an example of end-to-end application of this framework highlighting the computational benefits of a multi-fidelity approach.

Giuseppe Cataldo↗

Drought and Deluge: the Recurrence of Hydroclimate Extremes During the Past 600 Years in Eastern Australia’s Natural Resource Management (NRM) Clusters

Recent extremes of flood and drought across Australia have raised questions about the recurrence of such rare events and highlighted the importance of understanding multi-decadal climate variability. However, instrumental records over the past century are too short to adequately characterise climate variability on multi-decadal and longer timescales or robustly determine extreme event frequencies and their duration. Palaeoclimate reconstructions can provide much-needed information to help address this problem. Here, we use the 600-year hydroclimate record captured in the eastern Australian and New Zealand Drought Atlas (ANZDA) to analyse drought and pluvial frequency trends for East Australian Natural Resource Management (NRM) clusters. This partitioning of the drought atlas grid points into recognised biophysical areas (i.e. NRM clusters) revealed their differences and similarities in drought intensity and pluvial events over time. We find sustained multi-decadal periods of a wet–dry geographic 'seesaw' between eastern to central and southern NRMs (e.g. 1550–1600 CE and 1700–1750 CE). In contrast, other periods reveal spatially consistent wetting (e.g. 1500–1550 CE) or drying (e.g. 1750–1800 CE). Emerging hot spot analysis further shows that some areas that appear naturally buffered from severe drought during the instrumental period have a greater exposure risk when the longer 600-year record is considered. These findings are particularly relevant to management plans when dealing with the impacts of climate extremes developed at regional scales. Our results demonstrate that integrating and extending instrumental records with palaeoclimate datasets will become increasingly important for developing robust and locally specific extreme event frequency information for managing water resources.

Australian hydroclimate↗

Assimilation of Reconstructed Radiances from IASI Principal Component Scores into the GEOS-ADAS

Hyperspectral Infrared sounders such as IASI, AIRS, and CrIS have long been an integral part of radiance assimilation in numerical weather prediction (NWP), providing vertical profiles of water vapor and temperature information. Principal Component Scores (PCS) are a lossy form of compression that retains most information, such as temperature and moisture, by using a large training set of atmospheric profiles. However, PCS may not well represent profiles which are rare events, such as volcanic eruptions, and drops some sources of random noise. There has been an increased interest in the use of PCS as EUMETSAT plans to distribute future geostationary sounder radiances from MTG-IRS via PCS only. NWP centers use two approaches to deal with PCS: direct assimilation of the PCS by modifying the radiative transfer model to produce PCS and the associated Jacobians, or a simpler approach of decompressing the PCS and reconstructing the radiances back into channel space to allow assimilating radiances without modifications to the data assimilation system. EUMETSAT has developed a PCS product for IASI that has been operational since 2011. We utilize this product opting for the simpler approach, decompressing IASI PCS into channel space, and assimilating those radiances using the GEOS-ADAS. We then compare this with a control using the standard IASI radiance product. Resulting differences in global forecast statistics, differences in Forecast Sensitivity to Observation Impact, along with implications for implementation and quality control are discussed.

Bryan M. Karpowicz↗

Simulation of the 23 July 2012 Extreme Space Weather Event: What if This Extremely Rare CME Was Earth Directed?

Extreme space weather events are known to cause adverse impacts on critical modern day technological infrastructure such as high-voltage electric power transmission grids. On 23 July 2012, NASA's Solar Terrestrial Relations Observatory-Ahead (STEREO-A) spacecraft observed in situ an extremely fast coronal mass ejection (CME) that traveled 0.96 astronomical units (approx. 1 AU) in about 19 h. Here we use the SpaceWeather Modeling Framework (SWMF) to perform a simulation of this rare CME.We consider STEREO-A in situ observations to represent the upstream L1 solar wind boundary conditions. The goal of this study is to examine what would have happened if this Rare-type CME was Earth-bound. Global SWMF-generated ground geomagnetic field perturbations are used to compute the simulated induced geoelectric field at specific ground-based active INTERMAGNET magnetometer sites. Simulation results show that while modeled global SYM-H index, a high-resolution equivalent of the Dst index, was comparable to previously observed severe geomagnetic storms such as the Halloween 2003 storm, the 23 July CME would have produced some of the largest geomagnetically induced electric fields, making it very geoeffective. These results have important practical applications for risk management of electrical power grids.

SPACE WEATHER↗

Pan-Continental Droughts in North America over the Last Millennium

Regional droughts are common in North America, but pan-continental droughts extending across multiple regions, including the 2012 event, are rare relative to single-region events. Here, the tree-ring-derived North American Drought Atlas is used to investigate drought variability in four regions over the last millennium, focusing on pan-continental droughts. During the Medieval Climate Anomaly (MCA), the central plains (CP), Southwest (SW), and Southeast (SE) regions experienced drier conditions and increased occurrence of droughts and the Northwest (NW) experienced several extended pluvials. Enhanced MCA aridity in the SW and CP manifested as multidecadal megadroughts. Notably, megadroughts in these regions differed in their timing and persistence, suggesting that they represent regional events influenced by local dynamics rather than a unified, continental-scale phenomena. There is no trend in pan-continental drought occurrence, defined as synchronous droughts in three or more regions. SW, CP, and SE (SW+CP+SE) droughts are the most common, occurring in 12 percent of all years and peaking in prevalence during the twelfth and thirteenth centuries; patterns involving three other regions occur in about 8 percent of years. Positive values of the Southern Oscillation index (La Nina conditions) are linked to SW, CP, and SE (SW+CP+SE) droughts and SW, CP, and NW (SW+CP+NW) droughts, whereas CP, NW, and SE (CP+NW+SE) droughts are associated with positive values of the Pacific decadal oscillation and Atlantic multidecadal oscillation. While relatively rare, pan-continental droughts are present in the paleo record and are linked to defined modes of climate variability, implying the potential for seasonal predictability. Assuming stable drought teleconnections, these events will remain an important feature of future North American hydroclimate, possibly increasing in their severity in step with other expected hydroclimate responses to increased greenhouse gas forcing.

anomalies↗

Meteorites on Mars

Four types of meteoritic material should be found on Mars: (1) micrometeorites, many of which will survive atmospheric entry unmelted, which should fall relatively uniformly over the planet's surface, (2) ablation products from larger meteorites which ablate, break up and burn up in the Mars atmosphere, (3) debris from large, crater forming objects, which, by analogy to terrestrial and lunar impact events, will be concentrated in the crater ejecta blankets (except for rare, large events, such as the proposed C-T event on earth, which can distribute debris on a planetary scale), and (4) debris from the early, intense bombardment, which, in many areas of the planet, may now be incorporated into rocks by geologic processes subsequent to the intense bombardment era. To estimate the extent of meteoritic addition to indigenous Martian material, the meteoritic flux on Mars must be known. It is estimated that the overall flux is twice that for the Moon and 1.33 that for Earth. For small particles, whose orbital evolution is dominated by Poynting Robertson drag, the flux at Mars can be estimated from the Earth flux. The smaller Martian gravitational enhancement as well as the decrease in the spatial density of interplanetary dust with increasing heliocentric distance should reduce the flux of small particles at Mars to about 0.33 times the flux at Earth. Because of the smaller planetary cross-section the total infalling mass at Mars is then estimated to be 0.09 time the infalling mass in the micrometeorite size range at Earth.

Flynn, G. J.↗

Two classes of solar energetic particle events associated with impulsive and long duration soft X-ray flares

Solar energetic particle events observed in space have different properties depending on the class of associated flare. Impulsive flares, which occur low in the corona in regions of high energy density, are associated with particle events which are deficient in protons. These events are rarely associated with coronal mass ejections and interplanetary shocks. The vast majority of large, high energy proton events are associated with long duration flares, many of which are also associated with fast coronal mass ejections and strong interplanetary shocks. Such flare events originate relatively high in the corona.

Cane, H. V.↗

Adaptive Sampling of Time Series During Remote Exploration

This work deals with the challenge of online adaptive data collection in a time series. A remote sensor or explorer agent adapts its rate of data collection in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility (all its datapoints lie in the past) and limited control (it can only decide when to collect its next datapoint). This problem is treated from an information-theoretic perspective, fitting a probabilistic model to collected data and optimizing the future sampling strategy to maximize information gain. The performance characteristics of stationary and nonstationary Gaussian process models are compared. Self-throttling sensors could benefit environmental sensor networks and monitoring as well as robotic exploration. Explorer agents can improve performance by adjusting their data collection rate, preserving scarce power or bandwidth resources during uninteresting times while fully covering anomalous events of interest. For example, a remote earthquake sensor could conserve power by limiting its measurements during normal conditions and increasing its cadence during rare earthquake events. A similar capability could improve sensor platforms traversing a fixed trajectory, such as an exploration rover transect or a deep space flyby. These agents can adapt observation times to improve sample coverage during moments of rapid change. An adaptive sampling approach couples sensor autonomy, instrument interpretation, and sampling. The challenge is addressed as an active learning problem, which already has extensive theoretical treatment in the statistics and machine learning literature. A statistical Gaussian process (GP) model is employed to guide sample decisions that maximize information gain. Nonsta tion - ary (e.g., time-varying) covariance relationships permit the system to represent and track local anomalies, in contrast with current GP approaches. Most common GP models are stationary, e.g., the covariance relationships are time-invariant. In such cases, information gain is independent of previously collected data, and the optimal solution can always be computed in advance. Information-optimal sampling of a stationary GP time series thus reduces to even spacing, and such models are not appropriate for tracking localized anomalies. Additionally, GP model inference can be computationally expensive.

Thompson, David R.↗

Design of an Event-Driven Random-Access-Windowing CCD-Based Camera

Commercially available cameras are not design for the combination of single frame and high-speed streaming digital video with real-time control of size and location of multiple regions-of-interest (ROI). A new control paradigm is defined to eliminate the tight coupling between the camera logic and the host controller. This functionality is achieved by defining the indivisible pixel read out operation on a per ROI basis with in-camera time keeping capability. This methodology provides a Random Access, Real-Time, Event-driven (RARE) camera for adaptive camera control and is will suited for target tracking applications requiring autonomous control of multiple ROI's. This methodology additionally provides for reduced ROI read out time and higher frame rates compared to the original architecture by avoiding external control intervention during the ROI read out process.

event driven↗

Event-Driven Random-Access-Windowing CCD Imaging System

A charge-coupled-device (CCD) based high-speed imaging system, called a realtime, event-driven (RARE) camera, is undergoing development. This camera is capable of readout from multiple subwindows [also known as regions of interest (ROIs)] within the CCD field of view. Both the sizes and the locations of the ROIs can be controlled in real time and can be changed at the camera frame rate. The predecessor of this camera was described in High-Frame-Rate CCD Camera Having Subwindow Capability (NPO- 30564) NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 26. The architecture of the prior camera requires tight coupling between camera control logic and an external host computer that provides commands for camera operation and processes pixels from the camera. This tight coupling limits the attainable frame rate and functionality of the camera. The design of the present camera loosens this coupling to increase the achievable frame rate and functionality. From a host computer perspective, the readout operation in the prior camera was defined on a per-line basis; in this camera, it is defined on a per-ROI basis. In addition, the camera includes internal timing circuitry. This combination of features enables real-time, event-driven operation for adaptive control of the camera. Hence, this camera is well suited for applications requiring autonomous control of multiple ROIs to track multiple targets moving throughout the CCD field of view. Additionally, by eliminating the need for control intervention by the host computer during the pixel readout, the present design reduces ROI-readout times to attain higher frame rates. This camera (see figure) includes an imager card consisting of a commercial CCD imager and two signal-processor chips. The imager card converts transistor/ transistor-logic (TTL)-level signals from a field programmable gate array (FPGA) controller card. These signals are transmitted to the imager card via a low-voltage differential signaling (LVDS) cable assembly. The FPGA controller card is connected to the host computer via a standard peripheral component interface (PCI).

Monacos, Steve↗

Solar Flare and IMF Sector Structure Effects in the Lower Ionosphere

About 1% of all sudden ionospheric disturbances (SIDs) observed at the Panska Ves Observatory (Czechoslovakia), were found to be not of solar-XUV origin. Among them, the very rare SWF events (observed at L = 2.4) of corpuscular origin are the most interesting. The IMF sector structure effects in the midlatitude lower ionosphere are minor in comparison with effects of solar flares, geomagnetic storms, etc. There are two basic types of effects. The first type is a disturbance, best developed in geomagnetic activity, and observed in the night-time ionosphere. It can be interpreted as a response to sector structure related changes of geomagnetic (= magnetospheric) activity. The other type is best developed in the tropospheric vorticity area index and is also observed in the day-time ionosphere in winter. This effect is quietening in the ionosphere as well as troposphere. While the occurrence of the former type is persistent in time, the latter is severely diminished in some periods. All the stratosphere, the 10-mb level temperature and height above Berlin-Tempelhof do not display any observable IMF section structure effect.

Lastovicka, J.↗

The source of solar high-frequency acoustic modes - Theoretical expectations

The source exciting the solar p-modes is likely to be acoustic noise generated in the top part of the sun's convection zone. If so, then simple arguments suggest that most of the emitted energy may come from rare localized events that are well separated from one another in space and time. This note describes the acoustic emission that would be expected from such events, based on a ray-theory analysis. Most of the acoustic energy is found to emerge very close to the source, so that observations to identify emission events will require high spatial resolution.

Brown, Timothy M.↗

Solar flare nuclear gamma rays and interplanetary proton events

We compared flare gamma ray line (GRL) events and solar energetic proton (SEP) events for the period from Feb. 1980 - Jan. 1985 and substantiated earlier results showing a lack of correlation between gamma-ray-producing ions and interplanetary protons. This poor correlation results primarily from several large SEP events that originated in flares without detectable gamma ray emission. The converse case of GRL events unassociated with SEP events is rare. We present evidence which suggests that the ratio of trapped to escaping protons in GRL/SEP flares depends on the spatial scale size of the flare. We affirm the result of Bai and Dennis (1985) that GRL flares are generally accompanied (75 percent) by metric Type 2 bursts.

Cliver, E. W.↗

Nucleation and chiral symmetry breaking under controlled hydrodynamic flows

The effects of hydrodynamic convection on nucleation and broken chiral symmetry have been investigated for a simple inorganic molecule, sodium chlorate (NaClO3). Our experiment suggests that the symmetry breaking is a result of hydrodynamic amplification of rare nucleation events. The effect is more pronounced when the primary nucleation occurs on the solute-vapor interface, where mixing in the surface sublayer becomes important. The transition from the achiral to the chiral states appears to be smooth as the hydrodynamic parameters, such as flow rate, are varied.

Wu, Xiao-Lun↗