y0-causal-inference/y0
❓y0 (pronounced "why not?") is for causal inference in Python: a software library intended to support the scientific discovery process.
Hoyt, Charles Tapley↗
SEARCH · Search NASA
Results for “CAUSALITY”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Causal Interactions between Southern Ocean Polynyas and High-Latitude Atmosphere–Ocean Variability
Abstract Weddell Sea open-ocean polynyas have been observed to occasionally release heat from the deep ocean to the atmosphere, indicating that their sporadic appearances may be an important feature of high-latitude atmosphere–ocean variability. Yet, observations of the phenomenon are sparse and many standard-resolution models represent these features poorly, if at all. We use a fully coupled, synoptic-scale preindustrial control simulation of the Energy Exascale Earth System Model (E3SMv0-HR) to effectively simulate open-ocean polynyas and investigate their role in the climate system. Our approach employs statistical tests of Granger causality to diagnose local and remote drivers of, and responses to, polynya heat loss on interannual to decadal time scales. First, we find that polynya heat loss Granger causes a persistent increase in surface air temperature over the Weddell Sea, strengthening the local cyclonic wind circulation. Along with responding to polynyas, atmospheric conditions also facilitate their development. When the Southern Ocean experiences a rapid poleward shift in the circumpolar westerlies following a prolonged negative phase of the southern annular mode (SAM), Weddell Sea salinity increases, promoting density destratification and convection in the water column. Finally, we find that the reduction of surface heat fluxes during periods of full ice cover is not fully compensated by ocean heat transport into the high latitudes. This imbalance leads to a buildup of ocean heat content that supplies polynya heat loss. These results disentangle the complex, coupled climate processes that both enable the polynya’s existence and respond to it, providing insights to improve the representation of these highly episodic sea ice features in climate models.
Kaufman, Zachary S.↗
Final Fugitive Dust Control NOV Causal Report
On June 30, 2020, a Notice of Violation (NOV) was issued by the City of Albuquerque (COA) Environmental Health Department, Air Quality Program. The NOV identified two violations of New Mexico Administrative Code (NMAC) 20.11.20, Fugitive Dust Control, stemming from an August 30, 2019 inspection of the construction site at Sandia/New Mexico (SNL/NM) Building 812. After the August 30 inspection, a Post-Instruction Notification (PIN) was issued to the SNL Construction Facilities Manager. The PIN was acknowledged by Department 4722 and sent to the COA on September 13, 2020 via email. The PIN "Comply by" date was September 13, 2019 was transmitted by National Nuclear Security Administration/ Sandia Field Office (NNSA/SFO) to COA offices on November 12, 2019. The PIN response was 48 business days past due for various reasons which were explored during the causal analysis.
54 ENVIRONMENTAL SCIENCES↗
Causal Trends for Occurrences at Sandia National Laboratories
A variety of issues and occurrences are reported at Sandia National Laboratories every year. The challenge is to filter through these occurrences and determine whether there are any notable trends related to work planning and control processes and whether some of the common problems can be mitigated or prevented. The hope is that some of the more common issues can be improved through training, communication, and/or documentation. These causal trends may also help to improve current training and work planning and control processes by revealing some opportunities for improvement.
42 ENGINEERING↗
NTS-SS-SNL-NMSITE-2017-0004,"Contamination Monitor Left in Service After Inadequate Calibration" Causes Not Fully Addressed (ES&H Causal Analysis Report)
Sandia National Laboratories Radiation Protection department did not successfully address the causes leading to the issue NTS-SS-SNL-NMSITE-2017-0004, “Contamination Monitor Left in Service After Inadequate Calibration”, nor identify through the verification and validation process that corrective actions were not fully implemented and effective at addressing the issue(s). This report is the third causal in four years associated with the iPCM12 instrument and the Radiation Protection Instrumentation (RPI) organization within Radiation Protection (00628).
61 RADIATION PROTECTION AND DOSIMETRY↗
NTS-SS-SNL-NMSITE-2017-0004 "Contamination Monitor Left in Service After Inadequate Calibration" Causes Not Fully Addressed (Causal Analysis Report)
On June 5th, 2020 Sandia National Laboratories signed and recommended for closure the evidence package for the Noncompliance Tracking System NTS—SS-SNL-NMSITE-2017-0004, Contamination Monitor Left in Service After Inadequate Calibration. On July 16th, 2020 the Sandia Field Office sent a follow-up question list to the Radiation Protection Instrumentation Program Lead to clarify some points while reviewing the evidence package. The follow-up questions readily identified deficiencies with all three calibrations of the iPCM12 systems. On July 30th, 2020 Radiation Protection hosted a meeting to better understand the exact nature of the concerns, determine if the iPCM12 machines were out of calibration and therefore would have to be taken out of service. One result of this meeting was to determine if SNL could withdraw the evidence package. SNL transmitted a letter on August 26th, 2020 recalling the evidence package and committed to performing a thorough causal analysis and invoke the required issues management processes to ensure that corrective actions are sustained.
54 ENVIRONMENTAL SCIENCES↗
General features of the stellar matter equation of state from microscopic theory, new maximum-mass constraints, and causality
The profile of a neutron star probes a very large range of densities, from the density of iron up to several times the density of saturated nuclear matter, and thus no theory of hadrons can be considered reliable if extended to those regions. We emphasize the importance of taking contemporary ab initio theories of nuclear and neutron matter as the baseline for any extension method, which will unavoidably involve some degree of phenomenology. We discuss how microscopic theory, on the one end, with causality and maximum-mass constraints, on the other, set strong boundaries to the high-density equation of state. We present our latest neutron star predictions where we combine polytropic extensions and parametrizations guided by speed of sound considerations. The predictions we show include our baseline neutron star cooling curves.
chiral effective field theory↗
A Causal Approach to Integrate Component Health Data into System Reliability Models
Two of the challenges of current plant reliability approaches are the ability to integrate plant health data, and to support decision making. Condition based data and diagnostic/prognostic information are in fact not considered into plant reliability models to inform system engineers on the most critical components. Currently, the propagation of quantitative health data from the component to the system level is a challenge given the diverse nature/structure of the data. On the other hand, plant reliability methods (which are typically based on fault-trees or reliability block diagrams) can effectively propagate data from the component to the system level, but values of failure rates or failure probabilities are an approximated integral representation of the past industry-wide operational experience, and it neglects the present component health status (e.g., diagnostic and condition-based data) and health projection (when available from prognostic data). Our first claim is that system reliability models should propagate health information from the component to the system/plant level in order to provide a quantitative snapshot of system/plant health and identify the most critical components. Our second claim is that component health should be informed solely by that specific component current and historical performance data and should not be an approximated integral representation of the past industry-wide operational experience. This paper is directly supporting these two claims by proposing a different approach to perform reliability modeling which relies on available component diagnostic, prognostic and condition-based data to measure component health, and it propagates this information through fault tree models. The propagation of health data from the component to the system level is performed not in terms of probability, but in terms of margins where margin is defined as the “distance” between the present actual status and an undesired event (e.g., failure or unacceptable performance). Through a cause-effect lens, while classical reliability models target the effect associated to a component performance, a margin-based approach focuses on the cause of an undesired component performance (i.e., component health). Hence, thinking of reliability in terms of margins implies decision making based on causal reasoning. We will show how fault tree models can be solved using a margin language and how this process can effectively assist system engineers to identify the most critical components.
97 MATHEMATICS AND COMPUTING↗
Causality of the nonequilibrium correlation functions.
It is shown that the correct lowest-order two-particle correlation function solution to the Bogoliubov-Born-Green-Kirkwood-Yvon hierarchy is given via a Green's function whose Fourier transform satisfies the analyticity requirements for causality. The Bogoliubov adiabatic approximation is shown to imply a solution which is acausal. Extension to the s-particle correlation function is discussed.
Murphy, F. X.↗
A closed-loop causal model of workload based on a comparison of fuzzy and crisp measurements techniques
Fuzzy and crisp measurements of workload are compared for a tracking task that varied in bandwidth and order of control. Fuzzy measures are as powerful as crisp measures, and can under certain conditions give extra insights into workload causality. Both methods suggest that workload arises in a system in which effort, performance, difficulty, and task variables are linked in a closed loop. Marked individual differences were found. Future work on the fuzzy measurement of workload is justified.
Moray, Neville↗
On the causality of plasma permittivity
Causal solutions for effective relative complex permittivities of plasmas are derived. Both lossless and lossy plasmas are considered.
Cockrell, C. R.↗
Prediction and causal reasoning in planning
Nonlinear planners are often touted as having an efficiency advantage over linear planners. The reason usually given is that nonlinear planners, unlike their linear counterparts, are not forced to make arbitrary commitments to the order in which actions are to be performed. This ability to delay commitment enables nonlinear planners to solve certain problems with far less effort than would be required of linear planners. Here, it is argued that this advantage is bought with a significant reduction in the ability of a nonlinear planner to accurately predict the consequences of actions. Unfortunately, the general problem of predicting the consequences of a partially ordered set of actions is intractable. In gaining the predictive power of linear planners, nonlinear planners sacrifice their efficiency advantage. There are, however, other advantages to nonlinear planning (e.g., the ability to reason about partial orders and incomplete information) that make it well worth the effort needed to extend nonlinear methods. A framework is supplied for causal inference that supports reasoning about partially ordered events and actions whose effects depend upon the context in which they are executed. As an alternative to a complete but potentially exponential-time algorithm, researchers provide a provably sound polynomial-time algorithm for predicting the consequences of partially ordered events.
Dean, T.↗
Fast causal multicast
A new protocol is presented that efficiently implements a reliable, causally ordered multicast primitive and is easily extended into a totally ordered one. Intended for use in the ISIS toolkit, it offers a way to bypass the most costly aspects of ISIS while benefiting from virtual synchrony. The facility scales with bounded overhead. Measured speedups of more than an order of magnitude were obtained when the protocol was implemented within ISIS. One conclusion is that systems such as ISIS can achieve performance competitive with the best existing multicast facilities - a finding contradicting the widespread concern that fault-tolerance may be unacceptably costly.
Birman, Kenneth P.↗
Causal simulation and sensor planning in predictive monitoring
Two issues are addressed which arise in the task of detecting anomalous behavior in complex systems with numerous sensor channels: how to adjust alarm thresholds dynamically, within the changing operating context of the system, and how to utilize sensors selectively, so that nominal operation can be verified reliably without processing a prohibitive amount of sensor data. The approach involves simulation of a causal model of the system, which provides information on expected sensor values, and on dependencies between predicted events, useful in assessing the relative importance of events so that sensor resources can be allocated effectively. The potential applicability of this work to the execution monitoring of robot task plans is briefly discussed.
Doyle, Richard J.↗
Lightweight causal and atomic group multicast
The ISIS toolkit is a distributed programming environment based on support for virtually synchronous process groups and group communication. A suite of protocols is presented to support this model. The approach revolves around a multicast primitive, called CBCAST, which implements a fault-tolerant, causally ordered message delivery. This primitive can be used directly or extended into a totally ordered multicast primitive, called ABCAST. It normally delivers messages immediately upon reception, and imposes a space overhead proportional to the size of the groups to which the sender belongs, usually a small number. It is concluded that process groups and group communication can achieve performance and scaling comparable to that of a raw message transport layer. This finding contradicts the widespread concern that this style of distributed computing may be unacceptably costly.
Birman, Kenneth P.↗
Causal compensated perturbations in cosmology
A theoretical framework is developed to calculate linear perturbations in the gravitational and matter fields which arise causally in response to the presence of stiff matter sources in a FRW cosmology. It is shown that, in order to satisfy energy and momentum conservation, the gravitational fields of the source must be compensated by perturbations in the matter and gravitational fields, and the role of such compensation in containing the initial inhomogeneities in their subsequent evolution is discussed. A complete formal solution is derived in terms of Green functions for the perturbations produced by an arbitrary source in a flat universe containing cold dark matter. Approximate Green function solutions are derived for the late-time density perturbations and late-time gravitational waves in a universe containing a radiation fluid. A cosmological energy-momentum pseudotensor is defined to clarify the nature of energy and momentum conservation in the expanding universe.
Veeraraghavan, Shoba↗
Scheduling with partial orders and a causal model
In an ongoing project at Honeywell SRC, we are constructing a prototype scheduling system for a NASA domain using the 'Time Map Manager' (TMM). The TMM representations are flexible enough to permit the representation of precedence constraints, metric constraints between activities, and constraints relative to a variety of references (e.g., Mission Elapsed Time vs. Mission Day). The TMM also supports a simple form of causal reasoning (projection), dynamic database updates, and monitoring specified database properties as changes occur over time. The greatest apparent advantage to using the TMM is the flexibility added to the scheduling process: schedules are constructed by a process of 'iterative refinement,' in which scheduling decisions correspond to constraining an activity either with respect to another activity or with respect to one time line. The schedule becomes more detailed as activities and constraints are added. Undoing a scheduling decision means removing a constraint, not removing an activity from a specified place on the time line. For example, we can move an activity around on the time line by deleting constraints and adding new ones.
Boddy, Mark↗
Causal modeling and event-driven simulation for monitoring of continuous systems
We describe extensions to the traditional techniques for anomaly detection, as well as new anomaly detection techniques based on alternate models of what distinguishes normal from abnormal behavior. Some of these techniques are designed to capture anomalies at individual sensors; some detect anomalies across collections of sensors. To assist in reasoning about complex global behaviors, we construct and simulate a causal model of the physical system being monitored. These techniques have been tested on data from the ECLSS of Space Station Freedom (SSF) and are being applied in advanced monitoring prototypes for the SSF External Active Thermal Control System of SSF and the Environmental Emergency and Consumables Management subsystem of the Space Shuttle.
Doyle, Richard↗