Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Decision Support Techniques”

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.

At least 19 records

The design of aircraft using the decision support problem technique

The Decision Support Problem Technique for unified design, manufacturing and maintenance is being developed at the Systems Design Laboratory at the University of Houston. This involves the development of a domain-independent method (and the associated software) that can be used to process domain-dependent information and thereby provide support for human judgment. In a computer assisted environment, this support is provided in the form of optimal solutions to Decision Support Problems.

Mistree, Farrokh↗

A decision-based perspective for the design of methods for systems design

Organization of material, a definition of decision based design, a hierarchy of decision based design, the decision support problem technique, a conceptual model design that can be manufactured and maintained, meta-design, computer-based design, action learning, and the characteristics of decisions are among the topics covered.

Mistree, Farrokh↗

Online model-based diagnosis to support autonomous operation of an advanced life support system

This article describes methods for online model-based diagnosis of subsystems of the advanced life support system (ALS). The diagnosis methodology is tailored to detect, isolate, and identify faults in components of the system quickly so that fault-adaptive control techniques can be applied to maintain system operation without interruption. We describe the components of our hybrid modeling scheme and the diagnosis methodology, and then demonstrate the effectiveness of this methodology by building a detailed model of the reverse osmosis (RO) system of the water recovery system (WRS) of the ALS. This model is validated with real data collected from an experimental testbed at NASA JSC. A number of diagnosis experiments run on simulated faulty data are presented and the results are discussed.

Non-NASA Center↗

Compromise - An effective approach for the hierarchical design of structural systems

The use of the compromise decision support problem in hierarchical design of structural systems is described. The mathematical template that supports the underlying precepts of hierarchical design in the context of the decision support problem technique is presented. A structural example that demonstrates the efficacy of the approach is included.

Shupe, J. A.↗

A management information system to study space diets

A management information system (MIS), including a database management system (DBMS) and a decision support system (DSS), was developed to dynamically analyze the variable nutritional content of foods grown and prepared in an Advanced Life Support System (ALSS) such as required for long-duration space missions. The DBMS was designed around the known nutritional content of a list of candidate crops and their prepared foods. The DSS was designed to determine the composition of the daily crew diet based on crop and nutritional information stored in the DBMS. Each of the selected food items was assumed to be harvested from a yet-to-be designed ALSS biomass production subsystem and further prepared in accompanying food preparation subsystems. The developed DBMS allows for the analysis of the nutrient composition of a sample 20-day diet for future Advanced Life Support missions and is able to determine the required quantities of food needed to satisfy the crew's daily consumption. In addition, based on published crop growth rates, the DBMS was able to calculate the required size of the biomass production area needed to satisfy the daily food requirements for the crew. Results from this study can be used to help design future ALSS for which the integration of various subsystems (e.g., biomass production, food preparation and consumption, and waste processing) is paramount for the success of the mission.

NASA Discipline Life Support Systems↗

Online fault adaptive control for efficient resource management in Advanced Life Support Systems

This article presents the design and implementation of a controller scheme for efficient resource management in Advanced Life Support Systems. In the proposed approach, a switching hybrid system model is used to represent the dynamics of the system components and their interactions. The operational specifications for the controller are represented by utility functions, and the corresponding resource management problem is formulated as a safety control problem. The controller is designed as a limited-horizon online supervisory controller that performs a limited forward search on the state-space of the system at each time step, and uses the utility functions to decide on the best action. The feasibility and accuracy of the online algorithm can be assessed at design time. We demonstrate the effectiveness of the scheme by running a set of experiments on the Reverse Osmosis (RO) subsystem of the Water Recovery System (WRS).

NASA Discipline Life Support Systems↗

Quantifying the Importance of Selected Drought Indicators for the United States Drought Monitor

Using information theory, our study quantifies the importance of selected indicators for the U.S. Drought Monitor (USDM) maps. We use the technique of mutual information (MI) to measure the importance of any indicator to the USDM, and because MI is derived solely from the data, our findings are independent of any model structure (conceptual, physically-based, or empirical). We also compare these MIs against the drought representation effectiveness ratings in the North America Drought Indices and Indicators Assessment (NADIIA) survey for Koeppen climate zones. This reveals: [1] agreement between some ratings and our MI values (high for example indicators like Standardized Precipitation-Evapotranspiration Index or SPEI); [2] some divergences (for example, soil moisture has high ratings but near-zero MIs for ESA-CCI soil moisture in the Western U.S., indicating the need of another remotely sensed soil moisture source); and [3] new insights into the importance of variables such as Snow Water Equivalent (SWE) that are not included in sources like NADIIA. Further analysis of the MI results yields findings related to: [1] hydrological mechanisms (summertime SWE domination during individual drought events through snowmelt into the water-scarce soil); [2] hydroclimatic types (the top pair of inputs in the Western and non-Western regions are SPEIs and soil moistures respectively); and [3] predictability (high for the California 2012-2017 event, with longer-timescale indicators dominating). Finally, the high MIs between multiple indicators jointly and the USDM indicate potentially high drought forecasting accuracies achievable using only model-based inputs, and the potential for global drought monitoring using only remotely sensed inputs, especially for locations having insufficient in situ observations.

Drought↗

On Developing a Taxonomy for Multidisciplinary Design Optimization: A Decision-Based Perspective

In this paper, we approach MDO from a Decision-Based Design (DBD) perspective and explore classification schemes for designing complex systems and processes. Specifically, we focus on decisions, which are only a small portion of the Decision Support Problem (DSP) Technique, our implementation of DBD. We map coupled nonhierarchical and hierarchical representations from the DSP Technique into the Balling-Sobieski (B-S) framework (Balling and Sobieszczanski-Sobieski, 1994), and integrate domain-independent linguistic terms to complete our taxonomy. Application of DSPs to the design of complex, multidisciplinary systems include passenger aircraft, ships, damage tolerant structural and mechanical systems, and thermal energy systems. In this paper we show that Balling-Sobieski framework is consistent with that of the Decision Support Problem Technique through the use of linguistic entities to describe the same type of formulations. We show that the underlying linguistics of the solution approaches are the same and can be coalesced into a homogeneous framework with which to base the research, application, and technology MDO upon. We introduce, in the Balling-Sobieski framework, examples of multidisciplinary design, namely, aircraft, damage tolerant structural and mechanical systems, and thermal energy systems.

Lewis, Kemper↗

Compromise - An effective approach for conceptual aircraft design

The Decision Support Problem (DSP) technique for aircraft design is presently demonstrated through the development of a compromise DSP template for the conceptual design of subsonic transport aircraft. System variables are wing span and area, fuselage diameter and length, takeoff weight, and installed thrust. Such system constraints as range and wing loading are represented algebraically using standard subsonic aircraft theory, and economic efficiency is modeled in terms of rates-of-return. The DSP template thus obtained has been tested and validated using the known mission requirements and design constants of the B 727-200 airliner.

Mistree, Farrokh↗

Enabling Autonomous Space Mission Operations with Artificial Intelligence

For over 50 years, NASA's crewed missions have been confined to the Earth-Moon system, where speed-of-light communications delays between crew and ground are practically nonexistent. This ground-centered mode of operations, with a large, ground-based support team, is not sustainable for NASAs future human exploration missions to Mars. Future astronauts will need smarter tools employing Artificial Intelligence (AI) techniques make decisions without inefficient communication back and forth with ground-based mission control. In this talk we will describe several demonstrations of astronaut decision support tools using AI techniques as a foundation. These demonstrations show that astronauts tasks ranging from living and working to piloting can benefit from AI technology development.

Frank, Jeremy↗

The Use of NASA near Real-time and Archived Satellite Data to Support Disaster Assessment

With support from a NASA's Applied Sciences Program, The Short‐term Prediction Research and Transition (SPoRT) Center has explored a variety of techniques for utilizing archived and near real‐time NASA satellite data to support disaster assessment activities. MODIS data from the NASA Land Atmosphere Near Real‐time Capability for EOS currently provides true color and other imagery for assessment and potential applications including, but not limited to, flooding, fires, and tornadoes. In May 2013, the SPoRT Center developed unique power outage composites using the VIIRS Day/Night Band to represent the first clear sky view of damage inflicted upon Moore and Oklahoma City, Oklahoma following the devastating EF‐5 tornado that occurred on May 20. Pre‐event imagery provided by the NASA funded Web‐Enabled Landsat Data project offer a basis of comparison for monitoring post-disaster recovery efforts. Techniques have also been developed to generate products from higher resolution imagery from the recently available International Space Station SERVIR Environmental Research and Visualization System instrument. Of paramount importance is to deliver these products to end users expeditiously and in formats compatible with Decision Support Systems (DSS). Delivery techniques include a Tile Map Service (TMS) and a Web Mapping Service (WMS). These mechanisms allow easy integration of satellite products into DSS's, including the National Weather Service's Damage Assessment Toolkit for use by personnel conducting damage surveys. This poster will present an overview of the developed techniques and products and compare the strengths and weaknesses of the TMS and WMS.

McGrath, Kevin M.↗

Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS): A conceptual framework

In recent years there has been increasing interest in applying the computer based problem solving techniques of Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS) to analyze extremely complex problems. A conceptual framework is developed for successfully integrating these three techniques. First, the fields of AI, OR, and DSS are defined and the relationships among the three fields are explored. Next, a comprehensive adaptive design methodology for AI and OR modeling within the context of a DSS is described. These observations are made: (1) the solution of extremely complex knowledge problems with ill-defined, changing requirements can benefit greatly from the use of the adaptive design process, (2) the field of DSS provides the focus on the decision making process essential for tailoring solutions to these complex problems, (3) the characteristics of AI, OR, and DSS tools appears to be converging rapidly, and (4) there is a growing need for an interdisciplinary AI/OR/DSS education.

Parnell, Gregory S.↗

Fuzzy logic, neural networks, and soft computing

The past few years have witnessed a rapid growth of interest in a cluster of modes of modeling and computation which may be described collectively as soft computing. The distinguishing characteristic of soft computing is that its primary aims are to achieve tractability, robustness, low cost, and high MIQ (machine intelligence quotient) through an exploitation of the tolerance for imprecision and uncertainty. Thus, in soft computing what is usually sought is an approximate solution to a precisely formulated problem or, more typically, an approximate solution to an imprecisely formulated problem. A simple case in point is the problem of parking a car. Generally, humans can park a car rather easily because the final position of the car is not specified exactly. If it were specified to within, say, a few millimeters and a fraction of a degree, it would take hours or days of maneuvering and precise measurements of distance and angular position to solve the problem. What this simple example points to is the fact that, in general, high precision carries a high cost. The challenge, then, is to exploit the tolerance for imprecision by devising methods of computation which lead to an acceptable solution at low cost. By its nature, soft computing is much closer to human reasoning than the traditional modes of computation. At this juncture, the major components of soft computing are fuzzy logic (FL), neural network theory (NN), and probabilistic reasoning techniques (PR), including genetic algorithms, chaos theory, and part of learning theory. Increasingly, these techniques are used in combination to achieve significant improvement in performance and adaptability. Among the important application areas for soft computing are control systems, expert systems, data compression techniques, image processing, and decision support systems. It may be argued that it is soft computing, rather than the traditional hard computing, that should be viewed as the foundation for artificial intelligence. In the years ahead, this may well become a widely held position.

Zadeh, Lofti A.↗

Systems Engineering Techniques for ALS Decision Making

The Advanced Life Support (ALS) Metric is the predominant tool for predicting the cost of ALS systems. Metric goals for the ALS Program are daunting, requiring a threefold increase in the ALS Metric by 2010. Confounding the problem, the rate new ALS technologies reach the maturity required for consideration in the ALS Metric and the rate at which new configurations are developed is slow, limiting the search space and potentially giving the perspective of a ALS technology, the ALS Metric may remain elusive. This paper is a sequel to a paper published in the proceedings of the 2003 ICES conference entitled, "Managing to the metric: an approach to optimizing life support costs." The conclusions of that paper state that the largest contributors to the ALS Metric should be targeted by ALS researchers and management for maximum metric reductions. Certainly, these areas potentially offer large potential benefits to future ALS missions; however, the ALS Metric is not the only decision-making tool available to the community. To facilitate decision-making within the ALS community a combination of metrics should be utilized, such as the Equivalent System Mass (ESM)-based ALS metric, but also those available through techniques such as life cycle costing and faithful consideration of the sensitivity of the assumed models and data. Often a lack of data is cited as the reason why these techniques are not considered for utilization. An existing database development effort within the ALS community, known as OPIS, may provide the opportunity to collect the necessary information to enable the proposed systems analyses. A review of these additional analysis techniques is provided, focusing on the data necessary to enable these. The discussion is concluded by proposing how the data may be utilized by analysts in the future.

Rodriquez, Luis F.↗

Goal driven kinematic simulation of flexible arm robot for space station missions

Flexible arms offer a great degree of flexibility in maneuvering in the space environment. The problem of transporting an astronaut for extra-vehicular activity using a space station based flexible arm robot was studied. Inverse kinematic solutions of the multilink structure were developed. The technique is goal driven and can support decision making for configuration selection as required for stability and obstacle avoidance. Details of this technique and results are given.

Janssen, P.↗

Information prioritization for control and automation of space operations

The applicability of a real-time information prioritization technique to the development of a decision support system for control and automation of Space Station operations is considered. The steps involved in the technique are described, including the definition of abnormal scenarios and of attributes, measures of individual attributes, formulation and optimization of a cost function, simulation of test cases on the basis of the cost function, and examination of the simulation scenerios. A list is given comparing the intrinsic importances of various Space Station information data.

Ray, Asock↗

Methodology Development for Assessment of Spaceport Technology Returns and Risks

As part of Kennedy Space Center's (KSC's) challenge to open the space frontier, new spaceport technologies must be developed, matured and successfully transitioned to operational systems. R&D investment decisions can be considered from multiple perspectives. Near mid and far term technology horizons must be understood. Because a multitude of technology investment opportunities are available, we must identify choices that promise the greatest likelihood of significant lifecycle At the same time, the costs and risks of any choice must be well understood and balanced against its potential returns The problem is not one of simply rank- ordering projects in terms of their desirability. KSC wants to determine a portfolio of projects that simultaneously satisfies multiple goals, such as getting the biggest bang for the buck, supporting projects that may be too risky for private funding, staying within annual budget cycles without foregoing the requirements of a long term technology vision, and ensuring the development of a diversity of technologies that, support the variety of operational functions involved in space transportation. This work aims to assist in the development of in methods and techniques that support strategic technology investment decisions and ease the process of determining an optimal portfolio of spaceport R&D investments. Available literature on risks and returns to R&D is reviewed and most useful pieces are brought to the attention of the Spaceport Technology Development Office (STDO). KSC's current project management procedures are reviewed. It is found that the "one size fits all" nature of KSC's existing procedures and project selection criteria is not conducive to prudent decision-making. Directions for improving KSC's - procedures and criteria are outlined. With help of a contractor, STDO is currently developing a tool, named Change Management Analysis Tool (CMAT)/ Portfolio Analysis Tool (PAT), to assist KSC's R&D portfolio determination. A critical review of CMAT/PAT is undertaken. Directions for the improvement of this tool are provided. STDO and KSC intend to follow up on many, if not all, of the recommendations provided.

Joglekar, Prafulla↗