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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Multi-Parent Clustering Algorithms from Stochastic Grammar Data Models

We introduce a statistical data model and an associated optimization-based clustering algorithm which allows data vectors to belong to zero, one or several "parent" clusters. For each data vector the algorithm makes a discrete decision among these alternatives. Thus, a recursive version of this algorithm would place data clusters in a Directed Acyclic Graph rather than a tree. We test the algorithm with synthetic data generated according to the statistical data model. We also illustrate the algorithm using real data from large-scale gene expression assays.

Mjoisness, Eric↗
NASA NTRSDate not supplied

NASA’s Identified Risks of Adverse Outcomes Due to Inadequate Human Systems Integration Architecture in Human Spaceflight

The NASA Human System Risk Board (HSRB) has the overall responsibility for tracking the evolution of the top ~30 human system risks that it has identified to be associated with human spaceflight. As part of this process, the Board is charged with maintaining a consistent, integrated process to mitigate those risks, and developing evidence-based risk posture recommendations. One of the identified risks is due to inadequate human systems integration architecture (HSIA) and a driving factor of this risk is that given decreasing real-time ground support for execution of complex operations during future exploration missions, there is a possibility of adverse performance outcomes including that crew are unable to adequately respond to unanticipated critical malfunctions or detect safety critical procedural errors. The HSRB uses Directed Acyclic Graphs (DAGs) as a communication tool for describing how astronaut exposure to spaceflight hazards leads to meaningful mission-level health and performance outcomes and as the basis for understanding intermediate causal relationships between risk contributing factors and countermeasures that link hazards to outcomes. The HSIA risk DAG will be presented and described. Historically, critical malfunctions requiring Crew/MCC management occurred at a rate of 1.7 times per year for ISS averaged over the lifetime and 3-4 times per year in the burn in phase for the vehicle. These averages do not include EVA data, which greatly increases the incident rate. Prior experience from the Apollo program showed 10/11 crewed missions experienced significant anomalies where crew relied heavily on MCC expertise in real-time. These failure patterns are in line with those observed in other complex engineered systems (e.g., oil rigs, launch systems, commercial aviation, etc.) It is likely that general malfunction and error rates are > 10% for short duration missions (<30 days), based on past and current spaceflight operations data. Likelihood of adverse outcomes has the potential to increase as crew conduct work with new, complex systems and with less ground support. For Low Earth Orbit missions and Lunar missions less than 30 days, assuming minimal comm delays, disruptions and bandwidth limitations, malfunctions and errors can affect mission objectives and crew health but may be mitigated by ground support. For Lunar missions greater than 30 days and any potential Mars mission malfunctions and errors can have Loss of Crew and Loss of Mission consequences due to reduced ground support (communication delays, constraints and blackouts) for more complex operations, as well as reduced resupply and evacuation options.

Daniel M Buckland↗
NASA NTRSDate not supplied

NASA's Identified Risk of Adverse Outcomes due to Inadequate Human Systems Integration Architecture

The NASA Human System Risk Board (HSRB) is responsible for tracking the evolution of the top ~30 human system risks identified to be associated with human spaceflight. As part of this process, the Board is charged with maintaining a consistent, integrated process to evaluate those risks and developing evidence-based risk posture recommendations. Risks are ranked by likelihood and consequence. Intermediate causal relationships between risk contributing factors and countermeasures that link hazards to outcomes are described using Directed Acyclic Graphs (DAGs). The DAGs are also useful for identifying common factors and countermeasures across the top 30 risks as well as communicating how astronaut exposure to spaceflight hazards leads to meaningful mission-level health and performance outcomes. One of the top risks tracked by the HSRB is The Risk of Adverse Outcomes Due to Inadequate Human-Systems Integration Architecture (HSIA). This risk captures the possibility that due to decreasing real-time ground support during missions beyond LEO, crew will be unable to adequately respond to unanticipated critical malfunctions or detect safety-critical procedural errors. The HSIA risk is ranked red (high) for Lunar surface and Mars missions due to the probability of Loss of Crew and Loss of Mission consequences. This paper describes the evidence that supports the HSIA risk ranking and presents the central narrative of the HSIA risk DAG-- i.e., anomaly detection, diagnosis, intervention, and task performance. Characterizations of the current state of practice for each of the DAG’s central nodes and the future tools needed for successful anomaly response are provided.

human-systems integration architecture↗
NASA NTRSDate not supplied

Integrating Human System Information with the Systems Platform for Aggregating and Relating Capabilities (SPARC)

Within Human Health and Performance, there exists a wealth of human system information that’s used a regular basis in support of NASA human exploration objectives, but the challenge is that all of this information was stored in multiple different locations and organized for specific uses, limiting its effectiveness and straining communication across multiple groups. To address this challenge, our project, the Systems Platform for Aggregating and Relating Capabilities (SPARC) was tasked with developing a new NASA internal web application that aggregates and relates multiple programs’ human system products, such as technical standards, program requirements and verifications, human system risks, research and evidence, and exploration capabilities, into one centralized platform that addresses the needs of human health and performance from multiple different perspectives. Using agile development methodologies, user-experience (UX) driven design principles, data visualization, and a strong emphasis on continuous improvement though consistent stakeholder engagement, the SPARC project released a beta version in less than 4 months, broadly launched version 1.0.0 Agency-wide three months after the beta, and has over 180 users in the first year of development. Our second year of development will see us moving from our initial capabilities to increasingly robust and complex integrations and visualizations, including Directed Acyclical Graphs (DAGs), natural language processing (NLP) for dynamic generation of relationships between the sources of truth, and an expansion into hierarchical levels of system design in support of the human exploration programs.

Data science↗
NASA NTRS2023

Framework for Extensible, Asynchronous Task Scheduling (FEATS) in Fortran

Most parallel scientific programs contain compiler directives (pragmas) such as those from OpenMP, explicit calls to runtime library procedures such as those implementing the Message Passing Interface (MPI), or compiler-specific language extensions such as those provided by CUDA. By contrast, the recent Fortran standards empower developers to express parallel algorithms without directly referencing lower-level parallel programming models. Fortran’s parallel features place the language within the Partitioned Global Address Space (PGAS) class of programming models. When writing programs that exploit data-parallelism, application developers often find it straightforward to develop custom parallel algorithms. Problems involving complex, heterogeneous, staged calculations, however, pose much greater challenges. Such applications require careful coordination of tasks in a manner that respects dependencies prescribed by a directed acyclic graph. When rolling one’s own solution proves difficult, extending a customizable framework becomes attractive. The paper presents the design, implementation, and use of the Framework for Extensible Asynchronous Task Scheduling (FEATS), which we believe to be the first task-scheduling tool written in modern Fortran. We describe the benefits and compromises associated with choosing Fortran as the implementation language, and we propose ways in which future Fortran standards can best support the use case in this paper.

Modern Fortran↗
DOE OSTI2024

A Causal Approach to Model Validation and Calibration

This poster presents a novel method for validation and verification that focuses on identifying causal relationships between data elements, moving beyond traditional statistical and machine learning approaches. These methods employ causal discovery techniques to reveal the underlying mechanisms of data generation. The research utilizes structural causal models and directed acyclic graphs to depict causal relationships. This approach assists in achieving alignment between simulation models and reality.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Entropy-based feature selection for capturing impacts in Earth system models with abrupt forcing

This paper presents the development of a new entropy-based feature selection method for identifying and quantifying impacts. Here, impacts are defined as statistically significant differences in spatio-temporal fields when comparing datasets with and without an external forcing in an Earth system model. Temporal feature selection is performed by first computing the cross-fuzzy entropy to quantify similarity of patterns between two datasets and then applying changepoint detection to identify regions of statistically constant entropy. The method is used to capture temperate north surface cooling from a 9-member simulation ensemble of the Mt. Pinatubo volcanic eruption, which injected 10 Tg of SO 2 into the stratosphere. The results estimate a mean difference decrease in near surface air temperature of -0.560 K with a 99% confidence interval between -0.864 K and -0.257 K between April and November of 1992, one year following the eruption. A sensitivity analysis with decreasing SO 2 injection revealed that the impact is statistically significant at 5 Tg but not at 3 Tg. Using identified features, a dependency graph model based on a 9-day lag had significantly fewer nodes than a graph based on monthly means. Furthermore, this demonstrates our method’s ability to perform dimension reduction while still uncovering source-to-impact pathways.

Changepoint detection↗
NASA NTRS1989

Noiseless compression using non-Markov models

Adaptive data compression techniques can be viewed as consisting of a model specified by a database common to the encoder and decoder, an encoding rule and a rule for updating the model to ensure that the encoder and decoder always agree on the interpretation of the next transmission. The techniques which fit this framework range from run-length coding, to adaptive Huffman and arithmetic coding, to the string-matching techniques of Lempel and Ziv. The compression obtained by arithmetic coding is dependent on the generality of the source model. For many sources, an independent-letter model is clearly insufficient. Unfortunately, a straightforward implementation of a Markov model requires an amount of space exponential in the number of letters remembered. The Directed Acyclic Word Graph (DAWG) can be constructed in time and space proportional to the text encoded, and can be used to estimate the probabilities required for arithmetic coding based on an amount of memory which varies naturally depending on the encoded text. The tail of that portion of the text which was encoded is the longest suffix that has occurred previously. The frequencies of letters following these previous occurrences can be used to estimate the probability distribution of the next letter. Experimental results indicate that compression is often far better than that obtained using independent-letter models, and sometimes also significantly better than other non-independent techniques.

Blumer, Anselm↗
NASA NTRS1991

Scalable Performance Environments for Parallel Systems

As parallel systems expand in size and complexity, the absence of performance tools for these parallel systems exacerbates the already difficult problems of application program and system software performance tuning. Moreover, given the pace of technological change, we can no longer afford to develop ad hoc, one-of-a-kind performance instrumentation software; we need scalable, portable performance analysis tools. We describe an environment prototype based on the lessons learned from two previous generations of performance data analysis software. Our environment prototype contains a set of performance data transformation modules that can be interconnected in user-specified ways. It is the responsibility of the environment infrastructure to hide details of module interconnection and data sharing. The environment is written in C++ with the graphical displays based on X windows and the Motif toolkit. It allows users to interconnect and configure modules graphically to form an acyclic, directed data analysis graph. Performance trace data are represented in a self-documenting stream format that includes internal definitions of data types, sizes, and names. The environment prototype supports the use of head-mounted displays and sonic data presentation in addition to the traditional use of visual techniques.

Reed, Daniel A.↗