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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Sustainable Crop Cultivation in Space Analogs: A BRIDGES Methodology Perspective Through SpaCEA

Sustainable crop cultivation in space holds paramount significance for the support of life in future long-duration missions. This research explores the development and integration of innovative low-cost proof-of-concept (LC-POC) plant growth cabinets tailored for use in space analog missions. By outlining past and current efforts in space farming, this study introduces the SpaCEA Cabinet using BRIDGES framework, establishing a context for reproducible experiments and innovation in plant growth systems. The SpaCEA cabinets can either be delivered in flat packs or assembled on-site, employing cutting-edge methods like 3-D printing and laser cutting. The main objective is to assess how effectively these structures foster crop growth within analog environments while replicating conditions crucial for space exploration. Employing a multi-faceted approach encompassing technical and qualitative dimensions, this project integrates a qualitative investigation where representatives managing analog stations and analog astronauts will partake in interviews and questionnaires to discern specific requirements and challenges within these environments. Insights gained from these engagements will significantly define the final design parameters of updated SpaCEA plant growth cabinets. The practical applicability of these cabinets emphasizes ease of assembly and transportation, addressing the inherent spatial and logistical constraints associated with space missions. Furthermore, the BRIDGES framework ensures the standardization of hardware, software, and data-gathering elements within a unified structure, which utilizes cutting-edge manufacturing technologies for the prototyping and deployment of these cabinets. The anticipated outcomes of this research include the identification of key design considerations and technical specifications for plant growth cabinets tailored to space farming analog systems. This research is poised to contribute valuable knowledge to sustainable space exploration through the development of interoperable plant growth systems for analog environments, advancing research in space crop cultivation which will make up part of a larger bioregenerative life support system.

Advanced Life Support↗
NASA NTRS1986

Rail accelerators for space transportation: An experimental investigation

An experimental program was conducted at the Lewis Research Center with the objective of investigating the technical feasibility of rail accelerators for propulsion applications. Single-stage, plasma driven rail accelerators of small (4 by 6 mm) and medium (12.5 by 12.5 mm) bores were tested at peak accelerating currents of 50 to 450 kA. Streak-camera photography was used to provide a qualitative description of plasma armature acceleration. The effects of plasma blowby and varying bore pressure on the behavior of plasma armatures were studied.

Zana, L. M.↗
NASA NTRS1990

Simulation-based reasoning about the physical propagation of fault effects

The research described deals with the effects of faults on complex physical systems, with particular emphasis on aircraft and spacecraft systems. Given that a malfunction has occurred and been diagnosed, the goal is to determine how that fault will propagate to other subsystems, and what the effects will be on vehicle functionality. In particular, the use of qualitative spatial simulation to determine the physical propagation of fault effects in 3-D space is described.

Feyock, Stefan↗
NASA NTRS1996

An Analysis of NASA Technology Transfer

A review of previous technology transfer metrics, recommendations, and measurements is presented within the paper. A quantitative and qualitative analysis of NASA's technology transfer efforts is performed. As a relative indicator, NASA's intellectual property performance is benchmarked against a database of over 100 universities. Successful technology transfer (commercial sales, production savings, etc.) cases were tracked backwards through their history to identify the key critical elements that lead to success. Results of this research indicate that although NASA's performance is not measured well by quantitative values (intellectual property stream data), it has a net positive impact on the private sector economy. Policy recommendations are made regarding technology transfer within the context of the documented technology transfer policies since the framing of the Constitution. In the second thrust of this study, researchers at NASA Langley Research Center were surveyed to determine their awareness of, attitude toward, and perception about technology transfer. Results indicate that although researchers believe technology transfer to be a mission of the Agency, they should not be held accountable or responsible for its performance. In addition, the researchers are not well educated about the mechanisms to perform, or policies regarding, technology transfer.

Bush, Lance B.↗
NASA NTRSDate not supplied

Identifying Emerging Safety Threats Through Topic Modeling in the Aviation Safety Reporting System: A Covid-19 Study

The NASA Aviation Safety Reporting System (ASRS) is a voluntary, confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants, and others involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts, and a short descriptive synopsis is written to describe the safety issue. The de-identified reports are then disseminated to the aviation community in many ways, including via an online database, Safety Alert Bulletins, For Your Information Notices, and the CALLBACK newsletter. In this work, we consider whether we can improve the grouping, linking, and understanding of safety concerns through topic modeling. Specifically, we use topic modeling as a building block to identify emerging safety threats over time. This unsupervised approach, we argue, offers the flexibility to identify new emerging themes in this large dataset by constructing different timelines based on the content similarity of ASRS report narratives. This method's unsupervised nature improves upon related research, which is limited to pre-defined labels and therefore can not fully capture emerging safety threats. We apply our method to all ASRS reports in 2020 to assess if the generated timelines can highlight COVID-19 as it is emerging as a safety threat in incoming ASRS reports. We perform both a quantitative and qualitative evaluation of the automatically constructed timelines. The qualitative evaluation is performed by describing the evolution of top terms in the timelines, generated by our method, which we found explicitly convey the themes of COVID-19. Separately, we use a set of 1,213 COVID-19 reports from 2020 that were manually identified by ASRS analysts to quantitatively evaluate the COVID-19 reports distribution across the timelines. Our results have shown that COVID-19 emergence can be identified using the top terms that were generated by topic modeling. The top terms in topic modeling therefore can serve as a summary alternative to manually inspecting reports. Moreover, leveraging the manually identified COVID-19 reports, we found the manually identified timelines accounted for over 70% of the COVID-19 reports curated by the ASRS analysts, which demonstrates the potential of this approach for facilitating the understanding of safety concerns as they emerge and evolve. This method shows great potential to understand aerospace safety threats and other narrative- driven incident report databases.

ASRS↗
NASA NTRSDate not supplied

Identifying Emerging Safety Threats Through Topic Modeling in the Aviation Safety Reporting System: A COVID-19 Study

The NASA Aviation Safety Reporting System (ASRS) is a voluntary, confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants, and others involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts, and a short descriptive synopsis is written to describe the safety issue. The de-identified reports are then disseminated to the aviation community in many ways, including via an online database, Safety Alert Bulletins, For Your Information Notices, and the CALLBACK newsletter. In this work, we consider whether we can improve the grouping, linking, and understanding of safety concerns through topic modeling. Specifically, we use topic modeling as a building block to identify emerging safety threats over time. This unsupervised approach, we argue, offers the flexibility to identify new emerging themes in this large dataset by constructing different timelines based on the content similarity of ASRS report narratives. This method's unsupervised nature improves upon related research, which is limited to pre-defined labels and therefore can not fully capture emerging safety threats. We apply our method to all ASRS reports in 2020 to assess if the generated timelines can highlight COVID-19 as it is emerging as a safety threat in incoming ASRS reports. We perform both a quantitative and qualitative evaluation of the automatically constructed timelines. The qualitative evaluation is performed by describing the evolution of top terms in the timelines, generated by our method, which we found explicitly convey the themes of COVID-19. Separately, we use a set of 1,213 COVID-19 reports from 2020 that were manually identified by ASRS analysts to quantitatively evaluate the COVID-19 reports distribution across the timelines. Our results have shown that COVID-19 emergence can be identified using the top terms that were generated by topic modeling. The top terms in topic modeling therefore can serve as a summary alternative to manually inspecting reports. Moreover, leveraging the manually identified COVID-19 reports, we found the manually identified timelines accounted for over 70% of the COVID-19 reports curated by the ASRS analysts, which demonstrates the potential of this approach for facilitating the understanding of safety concerns as they emerge and evolve. This method shows great potential to understand aerospace safety threats and other narrative- driven incident report databases.

ASRS↗
DOE OSTI2025

A detailed study of pre-heating effects in electron beam melting powder bed fusion process

Metal-based additive manufacturing processes, such as powder bed fusion with electron beam (PBF-EB) process, also referred to as electron beam melting (EBM), can produce high-density parts with minimal residual stresses due to the uniform and coherent preheating of the powder bed. However, understanding and controlling the multiple stages of preheating is required to enable the production of high-quality, consistent parts of various materials. This work presents a large-scale, multi-layer, three-dimensional numerical analysis focused on studying the preheating stages for predicting thermal history during the PBF-EB process. The model follows a continuous multi-stage cyclic process, that incorporates all the main stages of the PBF-EB process for 316 L stainless steel. This includes the gradual deposition of a new powder layer, the first and second preheating levels of the powder bed, and the energy deposition during melting (excluding the actual melt-pool behavior simulation). The model employs an adaptive time-scaling approach that automatically adjusts the energy deposition for each solution time-increment. This allows for localized changes in time-resolution over an otherwise computationally expensive multi-layer procedure. The material property variations are also taken into account, with an emphasis on the subtle irreversible changes in powder effective thermal conductivity after the two requisite preheating stages of the powder bed. This effect is studied using simplified conductivity models from the literature for partially sintered powder, validated by a dedicated experiment and numerical simulation. The large-scale model is then used to estimate the actual temperatures during first and second preheating levels for 316 L steel, which is not yet fully supported commercially for PBF-EB. Model predictions are corroborated by experiments, using and analyzing IR images, taken at the completion of each layer by the machine’s built-in infrared camera. The current model also incorporates a qualitative assessment for the effects of conductivity change during pre-heating, as well as evaluates the applicability of the time-scaling approach.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Polymers from Levoglucosenone and Other Anhydrosugars (CRADA Final Report)

The goal of this work is to identify promising drop-in or novel polymers that can be produced from levoglucosenone (LGO), CyreneTM, or other anhydrous sugars. LGO is a potentially important feedstock for polymers produced from renewable sources and can be produced in high yields by the company Circa from the pyrolysis of cellulose and biomass. NLR has a long history with anhydrosugars, pyrolysis and biomass-based polymers and has recently developed machine learning (ML) tools for predicting polymer properties. The DOE has recently supported efforts to identify coproducts from pyrolysis of biomass and their use in the production of performance advantaged polymers. DOE is also supporting the development of ML and molecular modeling for predicting and understanding polymer properties. NLR will leverage this expertise and experience to map out the pathways to polymers from LGO, use ML to identify the properties of novel polymers and estimate the market application space. From this effort NLR will deliver a summary report that outlines the most promising pathways based on quantitative and qualitative metrics for producing polymers from LGO.

09 BIOMASS FUELS↗
NASA NTRS2005

Risk Management for Human Support Technology Development

NASA requires continuous risk management for all programs and projects. The risk management process identifies risks, analyzes their impact, prioritizes them, develops and carries out plans to mitigate or accept them, tracks risks and mitigation plans, and communicates and documents risk information. Project risk management is driven by the project goal and is performed by the entire team. Risk management begins early in the formulation phase with initial risk identification and development of a risk management plan and continues throughout the project life cycle. This paper describes the risk management approach that is suggested for use in NASA's Human Support Technology Development. The first step in risk management is to identify the detailed technical and programmatic risks specific to a project. Each individual risk should be described in detail. The identified risks are summarized in a complete risk list. Risk analysis provides estimates of the likelihood and the qualitative impact of a risk. The likelihood and impact of the risk are used to define its priority location in the risk matrix. The approaches for responding to risk are either to mitigate it by eliminating or reducing the effect or likelihood of a risk, to accept it with a documented rationale and contingency plan, or to research or monitor the risk, The Human Support Technology Development program includes many projects with independently achievable goals. Each project must do independent risk management, considering all its risks together and trading them against performance, budget, and schedule. Since the program can succeed even if some projects fail, the program risk has a complex dependence on the individual project risks.

jones, Harry↗
NASA NTRSDate not supplied

Advanced Materials for the Lunar Surface: Multiscale Computational Design of Refractory Alloys and Carbides

Emerging operational environments, such as the lunar surface, present novel challenges for NASA and drive the need for advanced materials in applications like fission surface power systems. To address these demands, computational materials science is rapidly evolving to augment or replace costly and hazardous empirical testing. Although materials selection at NASA remains predominantly experimentally driven, advanced simulation methodologies are being steadily integrated into the engineering lifecycle. This work details the application of multiscale simulation techniques—including first-principles calculations, CALPHAD, dislocation dynamics, and molecular dynamics—at NASA's Ames Research Center to evaluate advanced materials for extreme environments. First, we present contributions to the Space Nuclear Propulsion Project. Be-cause propellant channel coatings in nuclear thermal rockets must withstand high-pressure, high-temperature hydro-gen, optimizing these materials is critical. First-principles calculations were employed to establish a rigorous quantitative and qualitative understanding of the behavior of the refractory carbides ZrC, NbC, and their mixtures in high-enthalpy hydrogen environments. This necessitated the generation of high-fidelity thermodynamic models for both stoichiometric and carbon-depleted carbides, both with and without the presence of hydrogen. Furthermore, we highlight efforts under the Refractory Alloy Additive Manufacturing Build Optimization (RAAMBO) project, where existing and novel alloy compositions were assessed for additive manufacturing printability and subsequent performance in applications such as heat pipes and rocket nozzle extensions. This was accomplished through a comprehensive multiscale simulation framework that bridged the gap from the nanometer to the millimeter scale. Across both initiatives, rigorous validation against empirical data was prioritized. By systematically employing a verified and validated computational frame-work, we demonstrate how simulation effectively supports multidisciplinary engineering efforts, builds project-wide confidence, and drives critical materials development.

computational materials↗
DOE OSTI2022

Cation–Ligand Interactions Dictate Salt Partitioning and Diffusivity in Ligand-Functionalized Polymer Membranes

Membranes are an attractive alternative to current thermal separations due to their scalability and energy efficiency in desalinating water. Unfortunately, many of the conventional membrane materials available today are unable to differentiate between ionic solutes, especially alkali cations, compromising their use in ion–ion separations. Inspired by the ion-specific interactions exhibited by biological ion channels, recent research efforts have focused on synthesizing and characterizing new polymeric materials that incorporate ligands into polymer networks to bias solubility and/or diffusivity of one cationic species over another. Despite these efforts, little is known about the influence of incorporating ligands into polymer membranes on solubility and diffusivity of the complexing species. In this study, we first build a qualitative model of salt partitioning, diffusivity, and permeability in generic cation-complexing ligand-functionalized polymer membranes. Next, to validate our model and hypotheses, we perform atomistic molecular dynamics simulations of a 12-crown-4-functionalized membrane in the presence of alkali halide salts at low concentration. Generally, cation complexation enhances cation solubility but decreases diffusivity. Interestingly, the reduction in diffusivity is predicted to be larger than the enhancement in solubility for materials which operate by the mechanisms proposed in our physical picture, ultimately resulting in a reduction in the permeability of the selectively complexing ion.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Comparison of model- and full-scale wind-tunnel performance

Experimental results from the Integrated Systems Test of the upgraded National Full-Scale Aerodynamics Complex 40- by 80-ft wind tunnel located at NASA Ames Research Center, which took place in 1987, are compared with results obtained with a 1/50 scale model of the wind tunnel. Test-section flow characteristics, air-exchange performance, total pressure distributions, and wall-static pressure distributions obtained with the model- and full-scale facilities are compared. The 1/50-scale model data were used to predict qualitative performance trends of the full-scale facility during investigation of design changes. Despite large differences in scale and Reynolds number between the two tunnels, quantitative agreement between certain model and full-scale performance characteristics was quite good.

Smith, Brian E.↗
NASA NTRS1993

A study of ignition phenomena of bulk metals by radiant heating

Early research on combustion of metals was motivated by the knowledge of the large heat release and corresponding high temperatures associated with metal-oxygen reactions. The advent of space flight brought about an increased interest in the ignition and combustion of metallic particles as additives in solid rocket propellants. More recently, attention has been given to the flammability properties of bulk, structural metals due to the number of accidental explosions of metal components in high-pressure oxygen systems. The following work represents a preliminary study that is part of a broader research effort aimed at providing further insight into the phenomena of bulk metal combustion by looking at the effects of gravity on the ignition behavior of metals. The scope of this preliminary experimental study includes the use of a non-coherent, continuous radiation ignition source, the measurement of temperature profiles of a variety of metals and a qualitative observation of the ignition phenomena at normal gravity. The specific objectives of the investigation include: (1) a feasibility study of the use of a continuous radiation source for metal ignition; (2) testing and characterization of the ignition behavior of a variety of metals; and (3) building a preliminary experimental database on ignition of metals under normal gravity conditions.

Branch, Melvin C.↗
NASA NTRS2002

Synthetic Vision Systems in GA Cockpit-Evaluation of Basic Maneuvers Performed by Low Time GA Pilots During Transition from VMC to IMC

An experimental investigation was conducted to study the effectiveness of modern flight displays in general aviation cockpits for mitigating Low Visibility Loss of Control and the Controlled Flight Into Terrain accidents. A total of 18 General Aviation (GA) pilots with private pilot, single engine land rating, with no additional instrument training beyond private pilot license requirements, were recruited to evaluate three different display concepts in a fixed-based flight simulator at the NASA Langley Research Center's General Aviation Work Station. Evaluation pilots were asked to continue flight from Visual Meteorological Conditions (VMC) into Instrument Meteorological Conditions (IMC) while performing a series of 4 basic precision maneuvers. During the experiment, relevant pilot/vehicle performance variables, pilot control inputs and physiological data were recorded. Human factors questionnaires and interviews were administered after each scenario. Qualitative and quantitative data have been analyzed and the results are presented here. Pilot performance deviations from the established target values (errors) were computed and compared with the FAA Practical Test Standards. Results of the quantitative data indicate that evaluation pilots committed substantially fewer errors when using the Synthetic Vision Systems (SVS) displays than when they were using conventional instruments. Results of the qualitative data indicate that evaluation pilots perceived themselves to have a much higher level of situation awareness while using the SVS display concept.

Takallu, M. A.↗
NASA NTRS2019

Wind Tunnel Flow Field Visualizations of the Space Launch System Vehicle Ascent

A wind tunnel test was conducted to characterize the aeroacoustic environment of several configurations of the Space Launch System during ascent. The test was conducted in the 11-by-11 foot transonic and 9-by-7 foot supersonic test sections at NASA Ames research center. Throughout this experiment data was collected from several types of instrumentation including: dynamic and steady-state pressure sensors, unsteady and steady pressure sensitive paint, time-resolved shadowgraph and infrared imaging. The following details results and analysis from the time-resolved shadowgraph and infrared imaging data systems. The time-resolved shadowgraph provided a qualitative measurement of the near-field turbulent fluctuations. These results helped provide context to the relative magnitude and frequency content of the fluid-structure-interaction driving the surface pressure phenomena characterized by the discrete pressure transducers and unsteady pressure sensitive paint. The infrared imaging was used to verify boundary layer trip effectiveness and provide temperature correction for the unsteady pressure sensitive paint.

Shadowgraph↗
DOE OSTI2022

Cyber risk assessment and investment optimization using game theory and ML-based anomaly detection and mitigation for wide-area control in smart grids

The electric power grid is increasingly becoming susceptible to cyber attacks that exploit vulnerabilities in the smart grid control, information, and physical layers. Successful cyber attacks can have catastrophic impacts on the social and economic well-being of any nation all over the globe. It has, thus, become imperative to secure the smart grid against such adversarial actions to ensure stable, secure, and reliable operation of the grid. The existing research and industry practices prove to be inadequate in terms of providing pragmatic and effective defense methodologies and measures for long-term cybersecurity planning and real-time cybersecurity for grid operation. For example, existing works lack models that incorporate uncertain behavior of cyber-attackers and pragmatic defense measures for cyber risk assessment and cybersecurity investment optimization which often provide unreliable and strictly qualitative solutions to these problems. At the same time, with the growing number of cyber incidents in the grid, there still exists a need to develop attack-resilient algorithms for wide-area monitoring, protection, and control (WAMPAC) applications like the wide-area voltage control systems (WAVCS) for Flexible AC Transmissions Systems (FACTS) that lack in scalable and feasible solutions from the cybersecurity perspective. This dissertation proposes novel models and methodologies for: (1) Cybersecurity planning, and (2) Cybersecurity for system operation. The cybersecurity planning is achieved through cyber risk assessment and cybersecurity resource investment optimization for long-term cybersecurity of the grid using game theory and attack-defense trees. Cybersecurity for system operation consists of development of cyber anomaly detection and mitigation algorithms for flexible AC transmission system (FACTS) controller-based wide-area voltage control systems (WAVCS) using machine learning (ML), and software defined networking-based moving target defense network routing for achieving real-time cyber-physical security for grid operations. This is followed by hardware-in-the-loop (HIL) implementation and evaluation of these attack prevention, detection, and mitigation algorithms and methodologies showcasing their feasibility in a close to real-world environment. For cybersecurity planning, a novel approach involving a combination of game theory and attack defense trees (ADT) for optimal cybersecurity resource allocation in the smart grid is proposed. This methodology involves modeling of the cyber-physical smart grid substations as ADTs, defining attacker costs, defense costs, and attack probabilities for attack access points. Using game theoretical formulation, optimal defense strategies for the defender of the system to invest cybersecurity resources in the grid are obtained. Additionally, a game-theoretic framework is developed for quantitative cyber-physical risk assessment of the grid under a dynamically changing cyber threat space and uncertain behavior of cyber attackers which is further used to optimize investments in the smart grid's cybersecurity resources. The attacker, defender, and the smart grid system are modeled while incorporating attacker-stochasticity and federal guidelines for smart grid cybersecurity. This allows quantification of threat, vulnerabilities, and attack impact of the grid for quantitative risk assessment. The defender's budget to invest in the security resources in the grid is optimized based on the strategies leading to minimum system risk. The evaluation of the proposed solutions highlight the feasibility for practical implementation of these methodologies and algorithms in the smart grid, while taking the federal requirements and guidelines for smart grid security into consideration. For achieving cybersecurity for system operation, attack prevention, detection, and mitigation algorithms and methodologies are developed specifically for FACTS-based WAVCS. Anomaly detection and mitigation in the WAVCS are achieved using algorithms based on machine learning which involves offline training and testing of ML models with CPS datasets incorporating physics-based features that allow accurate distinction between system faults and cyber attacks. For attack prevention, a methodology based on software defined network (SDN)-based moving target defense (MTD) network routing is proposed that enables prevention of Denial of Service (DoS) type attacks on the smart grid communication system. Subsequently, these methodologies and algorithms are implemented and evaluated on an HIL testbed that allows for real-time attack prevention, detection, and mitigation of emulated cyber attacks on the WAVCS in a close to real-world environment. The results show highly accurate and efficient performance of the implemented algorithms and methodologies with the smart grid system operating within the NERC's system operation limits even in the presence of DoS and data integrity cyber attacks. This work opens up future research opportunities in other directions such as (1) Expanding cybersecurity planning methodologies to real-time cyber contingency analysis with different game formulations; and (2) Applying the cybersecurity for system operation algorithms to broader categories of wide-area control applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Meso- to microscale modeling of atmospheric stability effects on wind turbine wake behavior in complex terrain

Abstract. Terrain-induced flow phenomena modulate wind turbine performance and wake behavior in ways that are not adequately accounted for in typical wind turbine wake and wind plant design models. In this work, we simulate flow over two parallel ridges with a wind turbine on one of the ridges, focusing on conditions observed during the Perdigão field campaign in 2017. Two case studies are selected to be representative of typical flow conditions at the site, including the effects of atmospheric stability: a stable case where a mountain wave occurs (as in ∼ 50 % of the nights observed) and a convective case where a recirculation zone forms in the lee of the ridge with the turbine (as occurred over 50 % of the time with upstream winds normal to the ridgeline). We use the Weather Research and Forecasting Model (WRF), dynamically downscaled from the mesoscale (6.75 km resolution) to microscale large-eddy simulation (LES) at 10 m resolution, where a generalized actuator disk (GAD) wind turbine parameterization is used to simulate turbine wakes. We compare the WRF–LES–GAD model results to data from meteorological towers, lidars, and a tethered lifting system, showing good qualitative and quantitative agreement for both case studies. Significantly, the wind turbine wake shows different amounts of vertical deflection from the terrain and persistence downstream in the two stability regimes. In the stable case, the wake follows the terrain along with the mountain wave and deflects downwards by nearly 100 m below hub height at four rotor diameters downstream. In the convective case, the wake deflects above the recirculation zone over 40 m above hub height at the same downstream distance. Overall, the WRF–LES–GAD model is able to capture the observed behavior of the wind turbine wakes, demonstrating the model's ability to represent wakes over complex terrain for two distinct and representative atmospheric stability classes, and, potentially, to improve wind turbine siting and operation in hilly landscapes.

17 WIND ENERGY↗
NASA NTRS1994

Multi-objective decision-making under uncertainty: Fuzzy logic methods

Selecting the best option among alternatives is often a difficult process. This process becomes even more difficult when the evaluation criteria are vague or qualitative, and when the objectives vary in importance and scope. Fuzzy logic allows for quantitative representation of vague or fuzzy objectives, and therefore is well-suited for multi-objective decision-making. This paper presents methods employing fuzzy logic concepts to assist in the decision-making process. In addition, this paper describes software developed at NASA Lewis Research Center for assisting in the decision-making process. Two diverse examples are used to illustrate the use of fuzzy logic in choosing an alternative among many options and objectives. One example is the selection of a lunar lander ascent propulsion system, and the other example is the selection of an aeration system for improving the water quality of the Cuyahoga River in Cleveland, Ohio. The fuzzy logic techniques provided here are powerful tools which complement existing approaches, and therefore should be considered in future decision-making activities.

Hardy, Terry L.↗