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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 NTRS2006

Real-Time Diagnosis of Faults Using a Bank of Kalman Filters

A new robust method of automated real-time diagnosis of faults in an aircraft engine or a similar complex system involves the use of a bank of Kalman filters. In order to be highly reliable, a diagnostic system must be designed to account for the numerous failure conditions that an aircraft engine may encounter in operation. The method achieves this objective though the utilization of multiple Kalman filters, each of which is uniquely designed based on a specific failure hypothesis. A fault-detection-and-isolation (FDI) system, developed based on this method, is able to isolate faults in sensors and actuators while detecting component faults (abrupt degradation in engine component performance). By affording a capability for real-time identification of minor faults before they grow into major ones, the method promises to enhance safety and reduce operating costs. The robustness of this method is further enhanced by incorporating information regarding the aging condition of an engine. In general, real-time fault diagnostic methods use the nominal performance of a "healthy" new engine as a reference condition in the diagnostic process. Such an approach does not account for gradual changes in performance associated with aging of an otherwise healthy engine. By incorporating information on gradual, aging-related changes, the new method makes it possible to retain at least some of the sensitivity and accuracy needed to detect incipient faults while preventing false alarms that could result from erroneous interpretation of symptoms of aging as symptoms of failures. The figure schematically depicts an FDI system according to the new method. The FDI system is integrated with an engine, from which it accepts two sets of input signals: sensor readings and actuator commands. Two main parts of the FDI system are a bank of Kalman filters and a subsystem that implements FDI decision rules. Each Kalman filter is designed to detect a specific sensor or actuator fault. When a sensor or actuator fault occurs, large estimation errors are generated by all filters except the one using the correct hypothesis. By monitoring the residual output of each filter, the specific fault that has occurred can be detected and isolated on the basis of the decision rules. A set of parameters that indicate the performance of the engine components is estimated by the "correct" Kalman filter for use in detecting component faults. To reduce the loss of diagnostic accuracy and sensitivity in the face of aging, the FDI system accepts information from a steady-state-condition-monitoring system. This information is used to update the Kalman filters and a data bank of trim values representative of the current aging condition.

Kobayashi, Takahisa↗
NASA NTRS2010

Physics of Life: A Model for Non-Newtonian Properties of Living Systems

This innovation proposes the reconciliation of the evolution of life with the second law of thermodynamics via the introduction of the First Principle for modeling behavior of living systems. The structure of the model is quantum-inspired: it acquires the topology of the Madelung equation in which the quantum potential is replaced with the information potential. As a result, the model captures the most fundamental property of life: the progressive evolution; i.e. the ability to evolve from disorder to order without any external interference. The mathematical structure of the model can be obtained from the Newtonian equations of motion (representing the motor dynamics) coupled with the corresponding Liouville equation (representing the mental dynamics) via information forces. All these specific non-Newtonian properties equip the model with the levels of complexity that matches the complexity of life, and that makes the model applicable for description of behaviors of ecological, social, and economical systems. Rather than addressing the six aspects of life (organization, metabolism, growth, adaptation, response to stimuli, and reproduction), this work focuses only on biosignature ; i.e. the mechanical invariants of life, and in particular, the geometry and kinematics of behavior of living things. Living things obey the First Principles of Newtonian mechanics. One main objective of this model is to extend the First Principles of classical physics to include phenomenological behavior on living systems; to develop a new mathematical formalism within the framework of classical dynamics that would allow one to capture the specific properties of natural or artificial living systems such as formation of the collective mind based upon abstract images of the selves and non-selves; exploitation of this collective mind for communications and predictions of future expected characteristics of evolution; and for making decisions and implementing the corresponding corrections if the expected scenario is different from the originally planned one. This approach postulates that even a primitive living species possesses additional, non-Newtonian properties that are not included in the laws of Newtonian or statistical mechanics. These properties follow from a privileged ability of living systems to possess a self-image (a concept introduced in psychology) and to interact with it. The proposed mathematical system is based on the coupling of the classical dynamical system representing the motor dynamics with the corresponding Liouville equation describing the evolution of initial uncertainties in terms of the probability density and representing the mental dynamics. The coupling is implemented by the information-based supervising forces that can be associated with self-awareness. These forces fundamentally change the pattern of the probability evolution, and therefore, lead to a major departure of the behavior of living systems from the patterns of both Newtonian and statistical mechanics. This innovation is meant to capture the signature of life based only on observable behavior, not on any biochemistry. This will not prevent the use of this model for developing artificial living systems, as well as for studying some general properties of behavior of natural, living systems.

Zak, Michail↗
NASA NTRS2010

Propulsion Risk Reduction Activities for Non-Toxic Cryogenic Propulsion

The Propulsion and Cryogenics Advanced Development (PCAD) Project s primary objective is to develop propulsion system technologies for non-toxic or "green" propellants. The PCAD project focuses on the development of non-toxic propulsion technologies needed to provide necessary data and relevant experience to support informed decisions on implementation of non-toxic propellants for space missions. Implementation of non-toxic propellants in high performance propulsion systems offers NASA an opportunity to consider other options than current hypergolic propellants. The PCAD Project is emphasizing technology efforts in reaction control system (RCS) thruster designs, ascent main engines (AME), and descent main engines (DME). PCAD has a series of tasks and contracts to conduct risk reduction and/or retirement activities to demonstrate that non-toxic cryogenic propellants can be a feasible option for space missions. Work has focused on 1) reducing the risk of liquid oxygen/liquid methane ignition, demonstrating the key enabling technologies, and validating performance levels for reaction control engines for use on descent and ascent stages; 2) demonstrating the key enabling technologies and validating performance levels for liquid oxygen/liquid methane ascent engines; and 3) demonstrating the key enabling technologies and validating performance levels for deep throttling liquid oxygen/liquid hydrogen descent engines. The progress of these risk reduction and/or retirement activities will be presented.

Smith, Timothy D.↗
NASA NTRS2010

Propulsion Risk Reduction Activities for Nontoxic Cryogenic Propulsion

The Propulsion and Cryogenics Advanced Development (PCAD) Project s primary objective is to develop propulsion system technologies for nontoxic or "green" propellants. The PCAD project focuses on the development of nontoxic propulsion technologies needed to provide necessary data and relevant experience to support informed decisions on implementation of nontoxic propellants for space missions. Implementation of nontoxic propellants in high performance propulsion systems offers NASA an opportunity to consider other options than current hypergolic propellants. The PCAD Project is emphasizing technology efforts in reaction control system (RCS) thruster designs, ascent main engines (AME), and descent main engines (DME). PCAD has a series of tasks and contracts to conduct risk reduction and/or retirement activities to demonstrate that nontoxic cryogenic propellants can be a feasible option for space missions. Work has focused on 1) reducing the risk of liquid oxygen/liquid methane ignition, demonstrating the key enabling technologies, and validating performance levels for reaction control engines for use on descent and ascent stages; 2) demonstrating the key enabling technologies and validating performance levels for liquid oxygen/liquid methane ascent engines; and 3) demonstrating the key enabling technologies and validating performance levels for deep throttling liquid oxygen/liquid hydrogen descent engines. The progress of these risk reduction and/or retirement activities will be presented.

Smith, Timothy D.↗
NASA NTRS2012

Emergent Capabilities Converging into M and S 2.0

The continued operational environment complexity faced by the Department of Defense, despite a restricted resource environment, is a mandate for greater adaptability and availability in joint training. To address these constraints, this paper proposes a model for the potential integration of adaptability training, virtual world capabilities and immersive training into the wider Joint Live Virtual and Constructive (JLVC) Federation, supported by human, social, cultural and behavior modeling, and measurement and assessment. By fusing those capabilities and modeling and simulation enhancements into the JLVC federation, it will create a force who is more apt to arrive at and implement correct decisions, and more able to appropriately seize initiative in the field. The model would allow for the testing and training of capabilities and TTPs that cannot be reasonably explored to their logical conclusions in a 'live' environment, as well as enhance training fidelity for all echelons and tasks.

Reitz, Emilie↗
NASA NTRS2015

Human Research Program Human Health Countermeasures Element: Evidence Report - Artificial Gravity

The most serious risks of long-duration flight involve radiation, behavioral stresses, and physiological deconditioning. Artificial gravity (AG), by substituting for the missing gravitational cues and loading in space, has the potential to mitigate the last of these risks by preventing the adaptive responses from occurring. The rotation of a Mars-bound spacecraft or an embarked human centrifuge offers significant promise as an effective, efficient multi-system countermeasure against the physiological deconditioning associated with prolonged weightlessness. Virtually all of the identified risks associated with bone loss, muscle weakening, cardiovascular deconditioning, and sensorimotor disturbances might be alleviated by the appropriate application of AG. However, experience with AG in space has been limited and a human-rated centrifuge is currently not available on board the ISS. A complete R&D program aimed at determining the requirements for gravity level, gravity gradient, rotation rate, frequency, and duration of AG exposure is warranted before making a decision for implementing AG in a human spacecraft.

Clement, Gilles↗
NASA NTRS2017

An Overview of Recent Cryogenic Fluid Management Developments

Long-term storage, supply, and transfer of cryogenic fluids are critical capabilities needed to advance the human exploration of space. Technologies and advanced development programs have been pursued to address issues likely to confront the designers and developers of future cryogenic fluid management (CFM) subsystems and propulsion systems. NASA and aerospace industries have continued to conduct research and development for the propulsion applications of cryogenic fluids. From the well known in-space applications, to new applications involving superconducting motors within multiple different aircraft, and a renewed interest in production of oxygen on Mars, NASA continues to probe cryogenic applications within propulsion. This article presents brief reviews of several of the current CFM efforts to support future space missions. NASA GRC is currently focusing on understanding some of the finer points in the application of multilayer insulation. GRC recently finished the activation of a new calorimeter that operates at 20 K with a warm boundary that can operate either around 90 K or at 300 K. Current testing is focused on investigating multiple different seam concepts, initially between temperatures of 300 K and 20 K, and between 20 K and 90 K. One of the larger recent NASA investments has been on the Structural Heat Intercept, Insulation, and Vibration Experiment Rig (SHIIVER). SHIIVER is a 4 m diameter tank that is approximately 1/2 scale of the planned upper stage of the new Space Launch System (SLS) rocket. SHIIVER is focused on demonstrating the thermal benefits of multilayer insulation on the tank domes and boil-off vapor cooling on structural cylinders that hold the tank in-line on the rocket. It will also quantify any damage that may incur during the acoustic environment of over 160 decibels that SLS will experience on its trip to Earth orbit. In support of the possible production of oxygen out of the Mars' atmosphere, a team comprised of four NASA centers (GRC, MSFC, JSC, and KSC) collaborated to investigate multiple different hardware combinations, refrigeration cycles, and integration techniques to minimize power and mass of the storage and liquefaction system. Moreover, high efficiency, high capacity cryocoolers are an element of CFM which is essential for achieving NASA's future long duration missions. Currently in development is a 20W at 20K unit for use with liquid hydrogen. It is scheduled for delivery to NASA in the summer of 2017. Two Phase I SBIRS have recently concluded resulting in the preliminary design of two different 90K units, each having a refrigeration capacity of approximately 150W. Once the development efforts are complete, these high capacity 90K units will be integrated into the design of NASA's Liquid Oxygen (LOX)/Methane applications such as the Lander and Ascent Vehicles, or possibly an in-space stage. CFM technology is critical to the success of missions to Mars, Planetary Exploration, and In-Situ Resource Utilization (ISRU) for cryogenic propellant production. NASA is focusing on the development of CFM technologies needed to provide necessary data and relevant experience to support informed decisions on implementation of design of cryogenic systems for long term space missions. Lessons learned from the described CFM developments would lead to enhanced safety and reliability and enabling technologies which could allow NASA to meet future space exploration goals.

Hedayat, A.↗
NASA NTRS2020

Mars Sample Return Mission Concept Status

This paper will provide an overview of current concepts and options for the architecture and design of a Mars Sample Return Mission, including the Sample Retrieval Lander (SRL) (developed by NASA) and the Earth Return Orbiter (ERO) (developed by ESA) . Key mission objectives and the overall campaign will be described, including the mission’s concept of operations and a notional timeline from launch to entry, through surface operations, to delivery of the samples to Mars orbit and return to Earth. The overall SRL lander vehicle concept will be described, including current options being evaluated. Key lander element options that have been studied will be discussed, including the Mars Ascent Vehicle (MAV), Sample Fetch Rover (provided by ESA), Orbiting Sample container (OS), and sample tube transfer robotics systems. For the ERO the vehicle concept will be described including key interfaces with the Capture/Containment and Return System (CCRS). Specific challenges and approaches for addressing those challenges will be discussed, including key technical margins and backward planetary protection. The information provided about possible Mars sample return architectures is for planning and discussion purposes only. NASA has made no official decision to implement Mars sample return.

Muirhead, Brian K↗
NASA NTRS2020

Thermal Architecture of A Conceptual Mars Sample Return Lander during Cruise and on Mars

A Pre-Project team is currently studying a conceptual Mars Sample Return (MSR) architecture that would return samples collected by Mars 2020 to Earth. The basic architecture comprises of acquisition of these samples using a sample retrieval lander (SRL), which also would also house the Mars Ascent Vehicle (MAV) and Sample Fetch Rover (SFR). The MAV would put the orbiting sample container (OS) in a Martian orbit, which would then rendezvous with an Earth return orbiter (ERO) and be sent to Earth. This paper focuses on the SRL portion of the potential MSR campaign. The thermal architecture of this mission during cruise to Mars presents several challenges that pertain to the thermal control of the spacecraft and the lander/MAV/rover throughout cruise under varying thermal environments & operating conditions. Additionally, the control of these systems within their allowable operating temperature limits on the Martian surface is very challenging because of the large fluctuations in the environment, operating conditions and limited electrical power and energy availability. This paper will describe the thermal architecture for a potential SRL mission, the key thermal requirements and interfaces.It should be noted that the decision to implement MSR will not be finalized until NASA’s completion of the National Environmental Policy Act (NEPA) process. This document is being made available for information purposes only.

Nicholas, Austin↗
NASA NTRSDate not supplied

Analytical Needs in a Sample Receiving Facility: Input from the MSR Operation Definition Team

The return of scientifically selected samples from Mars would provide a rare opportunity forinvestigation with the full range of the latest technology available, but to take full advantageof this opportunity, it is important to plan ahead to ensure the pristine nature of the samplesupon arrival within the Earth environment until scientific investigations can begin.The NASA/ESA science community-driven MSR Science Planning Group – Phase 2 (MSPG2)delivered recommendations and guidance regarding curation (1) and science (2, 3) activities tobe performed on the samples under containment. High-level requirements for the infrastruc-ture were also developed by MSPG2 (4). In order to prepare infrastructure-targeted input forthe ESA and NASA facility studies planned in the 2022-2023 timeframe, the agency-led MSROperational Scenarios Definition Team (MOSDT) was assembled to conceptualize the sampleoperations that will inform future architecture teams. Emphasis was placed on the respon-sibility of MOSDT to use community-defined requirements and to represent the view of the international scientific community.All necessary and sufficient instruments and analytical needs described in MSPG2 were inte-grated in MOSDT main deliverable, the operational workflow (see Hays et al, this conference).In MSPG2, notional instruments were split between curation analytical needs, and objective-driven (time-sensitive and sterilization-sensitive) science analytical needs. In MOSDT, whilethe first phases of curation, “pre-Basic Characterization” and “Basic Characterization” wererather streamlined and separate from other analytical needs, “Preliminary Examination” and“Science” instruments were not always physically segregated. In addition to the necessary andsufficient instruments described by MSPG2, the MOSDT recommended additional supportequipment for sterilization, cleanliness and contamination monitoring.It was sometimes necessary for the MOSDT to rely on assumptions to integrate instruments inthe activity workflow. In general, the assumptions were very conservative to limit contaminationand cross-contamination risks. It is expected that future work to refine limits of contaminationwill enable optimization of instrumentation.The community was consulted during the course of the MOSDT work. This abstract’s aimis two-fold: on one hand, inform the scientific community and overall MSR stakeholders, tobring their attention on the analytical needs currently considered as necessary and sufficient;on the other hand, to solicit feedback from a larger community audience to optimize and refineanalytical needs during the next phases of MSR ground-segment preparation.Disclaimer: The decision to implement Mars Sample Return will not be finalized until NASA’scompletion of the program’s National Environmental Policy Act (NEPA) process. This docu-ment is being made available for informational purposes only.[1] Tait et al. (2021) Preliminary planning for Mars Sample Return (MSR) curation activities ina Sample Receiving Facility (SRF). Astrobiology in press, doi:10.1089/ast.2021.0105. [2] Toscaet al. (2021) Time-sensitive aspects of Mars Sample Return (MSR) science. Astrobiologyin press, doi:10.1089/ast.2021.0115. [3] Velbel et al. (2021) Planning implications relatedto sterilization-sensitive science investigations associated with Mars Sample Return (MSR).Astrobiology in press, doi:10.1089/ast.2021.0113. [4] Carrier et al. (2021) Science and curationconsiderations for the design of a Mars Sample Return (MSR) Sample Receiving Facility (SRF).Astrobiology in press, doi:10.1089/ast.2021.0110.

Mars Sample Return↗
NASA NTRSDate not supplied

Mars Sample Return – An Overview of the Capture, Containment and Return System

The Mars Sample Return campaign aims at bringing back soil, rock and atmospheric samples from Mars to Earth to answer key questions about Mars’ biological evolution by means of four missions. The first one, Mars 2020, landed on the red planet on February 18, 2021 and has to date collected a number of samples through the Perseverance rover. The three subsequent missions will recover the sample tubes, launch them into Mars orbit and transport them back to Earth. These missions are currently in the planning and design stages of development and represent an international effort comprising NASA, ESA and many industry partners. The work presented here provides an overview of the current design and concept of operations of the NASA-provided Capture, Containment, and Return System (CCRS), which is the payload of the ESA-provided Earth Return Orbiter (ERO). ERO will rendezvous with the orbiting samples and CCRS will capture them, contain them and robotically insert them into a capsule that will return the samples to Earth, the Earth Entry System (EES). Three days before arrival on Earth, CCRS will release the EES, which will fly through space, enter Earth’s atmosphere, descend on a well-defined trajectory and safely land at the Utah Test and Training Range. The decision to implement Mars Sample Return will not be finalized until NASA’s completion of the National Environmental Policy Act process. This document is being made available for information purposes only.

Mars Sample Return↗
NASA NTRSDate not supplied

Automation of the ICME Workflow Incorporating Material Digital Twins at Different Length Scales Within a Robust Information Management System

Recent successes in Integrated Computational Materials Engineering (ICME) have demonstrated the potential in designing fit-for-purpose materials for a given application in a cost and time efficient manner. However, the material design process must contain a level of automation in the material decision process, implementing some optimization algorithms, to truly enable the full benefits of ICME, particularly when considering materials at multiple length/time scales. In this work, we will demonstrate how the GRC ICME schema and Python framework automates a workflow that captures, analyzes, maintains, and disseminates the digital footprint in the context of tailoring resin material at the nanoscale of a woven composite Y-joint at the macroscale for an Aurora D8 double bubble fuselage. This digital footprint incorporates the interaction of both structural digital twins and material twins at various length scales.

Brandon L. Hearley↗
NASA NTRS2024

Evaluation of Machine Learning and Deep Learning Algorithms for Fire Prediction in Southeast Asia

Vegetation fires are prevalent in South/Southeast Asian countries, making fire prediction crucial due to their potential environmental, economic, and social impacts. Accurate predictions of fires facilitate timely interventions, helping to mitigate uncontrolled fires that can lead to biodiversity loss and air quality issues. In this study, we utilize VIIRS satellite-derived fire data alongside six machine learning and deep learning models—Simple Persistence, Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), CNN-LSTM, and ConvLSTM—to determine the most effective fire prediction model, using Root Mean Square Error (RMSE) as the metric. Our results indicate that the CNN model is the most reliable in regions with spatial dependencies, such as Brunei, Indonesia, Malaysia, the Philippines, Timor-Leste, and Thailand. Conversely, the ConvLSTM model excels in countries with complex spatiotemporal dynamics like Laos, Myanmar, and Vietnam. The CNN-LSTM hybrid model also performed well in Cambodia, suggesting a need for a balanced approach in areas requiring both spatial and temporal feature extraction. Furthermore, simpler models like Persistence and MLP showed limitations in capturing dynamic patterns and temporal dependencies. Our findings highlight the importance of evaluating models before implementing any decision support systems (DSS) in fire management. By tailoring models to specific regional fire data, we can enhance prediction accuracy and responsiveness, ultimately improving fire risk management in Southeast Asia and beyond.

Deep learning↗
NASA NTRS2023

Implementing the GEOSS Water Strategy: From Observations to Decisions

In 2014, The GEOSS Water Strategy – From Observations to Decisions was published and steps were taken to implement the Strategy’s recommendations. The Strategy highlighted priority areas where the application of Earth observations to water research and water management decisions would have significant scientific and societal benefits. This article reviews the implementation of the Strategy’s recommendations over the past eight years. After a review of the Strategy’s assessment of the needs for water observations and their applications, it then reviews actions taken in response to the Strategy’s recommendations in its four major themes: improved data acquisition for Essential Water Variables, research and product development, interoperability, and capacity development. It highlights significant achievements in the implementation of the Strategy including some motivated by factors beyond this Strategy, reviews actions taken by participating agencies and programs for each of the main themes and summarizes the remaining challenges in achieving the Strategy’s full implementation. The article not only is an update for the Water Community regarding the GEOSS Water Strategy, but it is also an example of how other communities could develop and promulgate a set of strategic recommendations, monitor progress, and carry out assessments of their effectiveness.

Earth observations↗
NASA NTRS2005

Model Checking Real Time Java Using Java PathFinder

The Real Time Specification for Java (RTSJ) is an augmentation of Java for real time applications of various degrees of hardness. The central features of RTSJ are real time threads; user defined schedulers; asynchronous events, handlers, and control transfers; a priority inheritance based default scheduler; non-heap memory areas such as immortal and scoped, and non-heap real time threads whose execution is not impeded by garbage collection. The Robust Software Systems group at NASA Ames Research Center has JAVA PATHFINDER (JPF) under development, a Java model checker. JPF at its core is a state exploring JVM which can examine alternative paths in a Java program (e.g., via backtracking) by trying all nondeterministic choices, including thread scheduling order. This paper describes our implementation of an RTSJ profile (subset) in JPF, including requirements, design decisions, and current implementation status. Two examples are analyzed: jobs on a multiprogramming operating system, and a complex resource contention example involving autonomous vehicles crossing an intersection. The utility of JPF in finding logic and timing errors is illustrated, and the remaining challenges in supporting all of RTSJ are assessed.

Lindstrom, Gary↗
NASA NTRS1988

A knowledge-based decision support system for payload scheduling

The role that artificial intelligence/expert systems technologies play in the development and implementation of effective decision support systems is illustrated. A recently developed prototype system for supporting the scheduling of subsystems and payloads/experiments for NASA's Space Station program is presented and serves to highlight various concepts. The potential integration of knowledge based systems and decision support systems which has been proposed in several recent articles and presentations is illustrated.

Floyd, Stephen↗
NASA NTRS1991

Single-chip microcontrollers for switchgear control

A switchgear controller utilizing a microcontroller is described. The primary goal was to mimic the functions and performance of the generic controller board with a microcontroller board which will cause the power automation system to consume less power. The code for the microcontroller implementation on a development board has been developed, and the signal conditioning for the signals to the microcontroller has been designed and tested. The implementation of this decision system for data gathering, command control, fault detection, and circuit protection, when compared to other implementations, provides more functions and better response while reducing weight, volume, and power consumption.

Watson, Karan↗
NASA NTRS1992

Fuzzy sets, rough sets, and modeling evidence: Theory and Application. A Dempster-Shafer based approach to compromise decision making with multiattributes applied to product selection

The Dempster-Shafer theory of evidence is applied to a multiattribute decision making problem whereby the decision maker (DM) must compromise with available alternatives, none of which exactly satisfies his ideal. The decision mechanism is constrained by the uncertainty inherent in the determination of the relative importance of each attribute element and the classification of existing alternatives. The classification of alternatives is addressed through expert evaluation of the degree to which each element is contained in each available alternative. The relative importance of each attribute element is determined through pairwise comparisons of the elements by the decision maker and implementation of a ratio scale quantification method. Then the 'belief' and 'plausibility' that an alternative will satisfy the decision maker's ideal are calculated and combined to rank order the available alternatives. Application to the problem of selecting computer software is given.

Dekorvin, Andre↗