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NASA NTRS2016

NASA Work Breakdown Structure (WBS) Handbook

The purpose of this document is to provide program/project teams necessary instruction and guidance in the best practices for Work Breakdown Structure (WBS) and WBS dictionary development and use for project implementation and management control. This handbook can be used for all types of NASA projects and work activities including research, development, construction, test and evaluation, and operations. The products of these work efforts may be hardware, software, data, or service elements (alone or in combination). The aim of this document is to assist project teams in the development of effective work breakdown structures that provide a framework of common reference for all project elements. The WBS and WBS dictionary are effective management processes for planning, organizing, and administering NASA programs and projects. The guidance contained in this document is applicable to both in-house, NASA-led effort and contracted effort. It assists management teams from both entities in fulfilling necessary responsibilities for successful accomplishment of project cost, schedule, and technical goals. Benefits resulting from the use of an effective WBS include, but are not limited to: providing a basis for assigned project responsibilities, providing a basis for project schedule and budget development, simplifying a project by dividing the total work scope into manageable units, and providing a common reference for all project communication.

Planning↗

NASA NTRS2021

NASA Work Breakdown Structure (WBS) Handbook

The purpose of this document is to provide program/project teams necessary instruction and guidance in the best practices for WBS and WBS dictionary development and use for project implementation and management control. This handbook can be used for all types of NASA projects and work activities including research, development, construction, test and evaluation, and operations. The products of these work efforts may be hardware, software, data, or service elements (alone or in combination). The aim of this document is to assist project teams in the development of effective work breakdown structures that provide a framework of common reference for all project elements. The WBS and WBS dictionary are effective management processes for planning, organizing, and administering NASA programs and projects. The guidance contained in this document is applicable to both in-house, NASA-led effort and contracted effort. It assists management teams from both entities in fulfilling necessary responsibilities for successful accomplishment of project cost, schedule, and technical goals. Benefits resulting from the use of an effective WBS include, but are not limited to: providing a basis for assigned project responsibilities, providing a basis for project schedule and budget development, simplifying a project by dividing the total work scope into manageable units, and providing a common reference for all project communication.

Christopher Lewis Sadler↗

NASA NTRS1984

An operational system for subject switching between controlled vocabularies: A computational linguistics approach

The NASA Lexical Dictionary (NLD), a system that automatically translates input subject terms to those of NASA, was developed in four phases. Phase One provided Phrase Matching, a context sensitive word-matching process that matches input phrase words with any NASA Thesaurus posting (i.e., index) term or Use reference. Other Use references have been added to enable the matching of synonyms, variant spellings, and some words with the same root. Phase Two provided the capability of translating any individual DTIC term to one or more NASA terms having the same meaning. Phase Three provided NASA terms having equivalent concepts for two or more DTIC terms, i.e., coordinations of DTIC terms. Phase Four was concerned with indexer feedback and maintenance. Although the original NLD construction involved much manual data entry, ways were found to automate nearly all but the intellectual decision-making processes. In addition to finding improved ways to construct a lexical dictionary, applications for the NLD have been found and are being developed.

Silvester, J. P.↗

NASA NTRS2005

Predictive Interfaces for Long-Distance Tele-Operations

We address the development of predictive tele-operator interfaces for humanoid robots with respect to two basic challenges. Firstly, we address automating the transition from fully tele-operated systems towards degrees of autonomy. Secondly, we develop compensation for the time-delay that exists when sending telemetry data from a remote operation point to robots located at low earth orbit and beyond. Humanoid robots have a great advantage over other robotic platforms for use in space-based construction and maintenance because they can use the same tools as astronauts do. The major disadvantage is that they are difficult to control due to the large number of degrees of freedom, which makes it difficult to synthesize autonomous behaviors using conventional means. We are working with the NASA Johnson Space Center's Robonaut which is an anthropomorphic robot with fully articulated hands, arms, and neck. We have trained hidden Markov models that make use of the command data, sensory streams, and other relevant data sources to predict a tele-operator's intent. This allows us to achieve subgoal level commanding without the use of predefined command dictionaries, and to create sub-goal autonomy via sequence generation from generative models. Our method works as a means to incrementally transition from manual tele-operation to semi-autonomous, supervised operation. The multi-agent laboratory experiments conducted by Ambrose et. al. have shown that it is feasible to directly tele-operate multiple Robonauts with humans to perform complex tasks such as truss assembly. However, once a time-delay is introduced into the system, the rate of tele\ioperation slows down to mimic a bump and wait type of activity. We would like to maintain the same interface to the operator despite time-delays. To this end, we are developing an interface which will allow for us to predict the intentions of the operator while interacting with a 3D virtual representation of the expected state of the robot. The predictive interface anticipates the intention of the operator, and then uses this prediction to initiate appropriate sub-goal autonomy tasks.

Wheeler, Kevin R.↗

NASA NTRS1983

The NASTRAN user's manual

All information directly associated with problem solving using the NASTRAN program is presented. This structural analysis program uses the finite element approach to structural modeling wherein the distributed finite properties of a structure are represented by a finite element of structural elements which are interconnected at a finite number of grid points, to which loads are applied and for which displacements are calculated. Procedures are described for defining and loading a structural model. Functional references for every card used for structural modeling, the NASTRAN data deck and control cards, problem solution sequences (rigid formats), using the plotting capability, writing a direct matrix abstraction program, and diagnostic messages are explained. A dictionary of mnemonics, acronyms, phrases, and other commonly used NASTRAN terms is included.

Source record↗

NASA NTRS1974

Earth Observatory Satellite system definition study. Report no. 3: Design/cost tradeoff studies. Appendix A: EOS program WBS dictionary. Appendix B: EOS mission functional analysis

The work breakdown structure (WBS) dictionary for the Earth Observatory Satellite (EOS) is defined. The various elements of the EOS program are examined to include the aggregate of hardware, computer software, services, and data required to develop, produce, test, support, and operate the space vehicle and the companion ground data management system. A functional analysis of the EOS mission is developed. The operations for three typical EOS missions, Delta, Titan, and Shuttle launched are considered. The functions were determined for the top program elements, and the mission operations, function 2.0, was expanded to level one functions. Selection of ten level one functions for further analysis to level two and three functions were based on concern for the EOS operations and associated interfaces.

Source record↗

NASA NTRS1981

Office of Space Terrestrial Applications (OSTA)/Applications Data Service (ADS) data systems standards

Standards needed to interconnect applications data service pilots for data sharing were identified. Current pilot methodologies are assessed. Recommendations for future work are made. A preliminary set of requirements for guidelines and standards for catalogues, directories, and dictionaries was identified. The user was considered to be a scientist at a terminal. Existing and emerging national and international telecommunication standards were adopted where possible in view of new and unproven standards.

Walton, B. A.↗

NASA NTRS2021

Constrained Inversion of a Microwave Snowpack Emission Model Using Dictionary Matching: Applications for GPM Satellite

This article presents a new algorithmic framework for multilayer inversion of the dense media radiative transfer (DMRT) equations of snowpack emission, with particular emphasis on the role of high-frequency microwave channels above 60 GHz. The approach relies on dictionary matching and locally constrained least squares. The results demonstrate that the algorithm can invert the DMRT model and retrieve depth, density, and grain size of a single-layer snowpack when dependencies of density and grain size on depth are properly accounted for. However, as the number of layers increases, the sensitivity of the inversion to observation noise grows markedly. Using observations, over the Great Plains in the United States, from the microwave imager onboard the global precipitation measurement (GPM, 10-166 GHz) core satellite, the initial results demonstrate that under a clear-sky condition and no vegetation canopy, the algorithm is capable to retrieve the snow depth and water equivalent of seasonal snow with a mean absolute error (MAE) of less than 0.15 m--when compared to the high-resolution analysis data from the SNOw Data Assimilation System (SNODAS).

Snow↗

NASA NTRSDate not supplied

Enhancing NASA Earth Science Data Discovery from Scientific Publications

Earth observations from space borne instruments have evolved explosively in the past decades. Following closely are reanalysis systems assimilating model and observational data, yielding even longer records and larger number of variables. Thanks to advances in internet technology, it is now easier than ever to visualize and analyze these data using web interfaces. On the other hand, it also becomes an increasingly daunting task to build upon the existing knowledge published in various peer reviewed sources, and navigate toward the most relevant data, analysis, and visualization. We present an analysis of a subset of publications that utilized a popular visualization web interface at the NASA Goddard Earth Science Data and Information Services Center. Known as "Giovanni", it allows researchers from wide backgrounds to work with hundreds of variables from space observations and assimilation systems. Since coming online more than a decade ago, Giovanni has been credited in more than 100 papers per year, and the total count now is estimated to be nearly 1,500. Many of these papers contain valuable information about when, where and how Giovanni has been used, and hence forge an opportunity to learn and share the knowledge of which variables were used for what research projects. The purpose of our work is to retrieve the information from the papers and organize it as a knowledge repository which links together datasets, variables, places, dates and phenomena all of which reflect the essence of the published research. Since the publications are unstructured texts, we use natural language processing along with machine learning methods in the retrieval process. One of the challenges is deciphering the dataset names, because in many cases researchers refer to variables, rather than the datasets containing them. To constrain the number of terms, we deploy Earth Science ontologies as dictionaries for the term extraction. We demonstrate that storing these terms and underlying ontologies, along with datasets, variables and papers in the knowledge graph database, enables various linkages between all these entities facilitating the data discovery. Thus, we are setting a qualitatively new stage in improvements of web data interfaces, where machine learning techniques are used to establish and optimize usage-based discovery of data.

Irina V Gerasimov↗

NASA NTRS2001

Integrated Workforce Planning Model: A Proof of Concept

Recently, the Workforce and Diversity Management Office at KSC have launched a major initiative to develop and implement a competency/skill approach to Human Resource management. As the competency/skill dictionary is being elaborated, the need for a competency-based workforce-planning model is recognized. A proof of concept for such a model is presented using a multidimensional data model that can provide the data infrastructure necessary to drive intelligent decision support systems for workforce planing. The components of competency-driven workforce planning model are explained. The data model is presented and several schemes that would support the workforce-planning model are presented. Some directions and recommendations for future work are given.

Guruvadoo, Eranna K.↗

NASA NTRS2017

Study of Tools for Command and Telemetry Dictionaries

The Command and Telemetry Dictionary is at the heart of space missions. The C&T Dictionary represents all of the information that is exchanged between the various systems both in space and on the ground. Large amounts of ever-changing information has to be disseminated to all for the various systems and sub-systems throughout all phases of the mission. The typical approach of having each sub-system manage it's own information flow, results in a patchwork of methods within a mission. This leads to significant duplication of effort and potential errors. More centralized methods have been developed to manage this data flow. This presentation will compare two tools that have been developed for this purpose, CCDD and SCIMI that were designed to work with the Core Flight System (cFS).

Command Telemetry Dictionary C&↗

NASA NTRS1990

A flight expert system for on-board fault monitoring and diagnosis

An architecture for a flight expert system (FLES) to assist pilots in monitoring, diagnosing, and recovering from inflight faults is described. A prototype was implemented and an attempt was made to automate the knowledge acquisition process by employing a learning by being told methodology. The scope of acquired knowledge ranges from domain knowledge, including the information about objects and their relationships, to the procedural knowledge associated with the functionality of the mechanisms. AKAS (automatic knowledge acquisition system) is the constructed prototype for demonstration proof of concept, in which the expert directly interfaces with the knowledge acquisition system to ultimately construct the knowledge base for the particular application. The expert talks directly to the system using a natural language restricted only by the extent of the definitions in an analyzer dictionary, i.e., the interface understands a subset of concepts related to a given domain. In this case, the domain is the electrical system of the Boeing 737. Efforts were made to define and employ heuristics as well as algorithmic rules to conceptualize data produced by normal and faulty jet engine behavior examples. These rules were employed in developing the machine learning system (MLS). The input to MLS is examples which contain data of normal and faulty engine behavior and which are obtained from an engine simulation program. MLS first transforms the data into discrete selectors. Partial descriptions formed by those selectors are then generalized or specialized to generate concept descriptions about faults. The concepts are represented in the form of characteristic and discriminant descriptions, which are stored in the knowledge base and are employed to diagnose faults. MLS was successfully tested on jet engine examples.

Ali, Moonis↗

NASA NTRS2018

NASA Work Breakdown Structure (WBS) Handbook

Schedule↗

NASA NTRS2019

NASA Work Breakdown Structure (WBS) Handbook

Formulation↗

NASA NTRS1971

Users manual for the Variable dimension Automatic Synthesis Program (VASP)

A dictionary and some problems for the Variable Automatic Synthesis Program VASP are submitted. The dictionary contains a description of each subroutine and instructions on its use. The example problems give the user a better perspective on the use of VASP for solving problems in modern control theory. These example problems include dynamic response, optimal control gain, solution of the sampled data matrix Ricatti equation, matrix decomposition, and pseudo inverse of a matrix. Listings of all subroutines are also included. The VASP program has been adapted to run in the conversational mode on the Ames 360/67 computer.

White, J. S.↗

NASA NTRS2000

Ubiquitous CM and DM

Ubiquitous is a real word. I thank a former Total Quality Coach for my first exposure some years ago to its existence. My version of Webster's dictionary defines ubiquitous as "present, or seeming to be present, everywhere at the same time; omnipresent." While I believe that God is omnipresent, I have come to discover that CM and DM are present everywhere. Oh, yes; I define CM as Configuration Management and DM as either Data or Document Management. Ten years ago, I had my first introduction to the CM world. I had an opportunity to do CM for the Space Station effort at the NASA Lewis Research Center. I learned that CM was a discipline that had four areas of focus: identification, control, status accounting, and verification. I was certified as a CMIl graduate and was indoctrinated about clear, concise, and valid. Off I went into a world of entirely new experiences. I was exposed to change requests and change boards first hand. I also learned about implementation of changes, and then of technical and CM requirements.

Crowley, Sandra L.↗

NASA NTRS2013

A Framework to Debug Diagnostic Matrices

Diagnostics is an important concept in system health and monitoring of space operations. Many of the existing diagnostic algorithms utilize system knowledge in the form of diagnostic matrix (D-matrix, also popularly known as diagnostic dictionary, fault signature matrix or reachability matrix) gleaned from physical models. But, sometimes, this may not be coherent to obtain high diagnostic performance. In such a case, it is important to modify this D-matrix based on knowledge obtained from other sources such as time-series data stream (simulated or maintenance data) within the context of a framework that includes the diagnostic/inference algorithm. A systematic and sequential update procedure, diagnostic modeling evaluator (DME) is proposed to modify D-matrix and wrapper logic considering least expensive solution first. This iterative procedure includes conditions ranging from modifying 0s and 1s in the matrix, or adding/removing the rows (failure sources) columns (tests). We will experiment this framework on datasets from DX challenge 2009.

Model-based↗

NASA NTRS1979

The 25 kW power module evolution study. Part 3: Conceptual design for power module evolution. Volume 6: WBS and dictionary

Program elements of the power module (PM) system, are identified, structured, and defined according to the planned work breakdown structure. Efforts required to design, develop, manufacture, test, checkout, launch and operate a protoflight assembled 25 kW, 50 kW and 100 kW PM include the preparation and delivery of related software, government furnished equipment, space support equipment, ground support equipment, launch site verification software, orbital verification software, and all related data items.

Source record↗