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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Cayley fuzzy graphs on the fuzzy groups

Given non-trivial group G and a non-empty subset S of G such that not containing the identity element of G and S=S{sup −1}:={s"−"1∣s∈S}, the Cayley graph Γ=Cay(G,S) is the graph whose vertex set V(Γ) is G, and edge set E(Γ) is {{g,sg}∣g∈G,s∈S}. The Cayley graphs are presently being considered as models architecture for interconnection networks. When there is an uncertainty on vertices or edges, fuzzy graph has special importance. In this paper, we develop the concept of Cayley fuzzy graphs on the fuzzy groups and investigate some basic properties of Cayley fuzzy graphs. We introduce some sufficient conditions on the fuzzy graphs that under it’s, a fuzzy graph is a Cayley fuzzy graph and discuss some operations of the fuzzy graphs on the Cayley fuzzy graphs, prove that the product of two Cayley fuzzy graphs is a Cayley fuzzy graph, for some products. Also we provide an application of Cayley fuzzy graphs, and use Dijkstra’s Algorithm for finding the fuzzy shortest path in a Cayley fuzzy graph.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Generalized roughness in fuzzy filters and fuzzy ideals with thresholds in ordered semigroups

In the present paper, concept of roughness for fuzzy filters with thresholds (u{sub 1},u{sub 2}) in ordered semigroups is introduced. Then, this concept is extended to fuzzy bi-filters with thresholds and fuzzy quasi-filters with thresholds. Further approximations of fuzzy ideals with thresholds, fuzzy bi-ideals with thresholds, and fuzzy interior ideals with thresholds are studied. Moreover, this concept is applied to study approximations of fuzzy quasi-ideals with thresholds and semiprime fuzzy quasi-ideals with thresholds.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Covalent Functionalization of Silicon with Plasma-Grown “Fuzzy” Graphene: Robust Aqueous Photoelectrodes for CO 2 Reduction by Molecular Catalysts

Carbon electrodes are ideal for electrochemistry with molecular catalysts, exhibiting facile charge transfer and good stability. Yet for solar-driven catalysis with semiconductor light absorbers, stable semiconductor/carbon interfaces can be difficult to achieve, and carbon’s high optical extinction means it can only be used in ultrathin layers. Here, we demonstrate a plasma-enhanced chemical vapor deposition process that achieves well-controlled deposition of out-of-plane “fuzzy” graphene (FG) on thermally oxidized Si substrates. The resulting Si|FG interfaces possess a silicon oxycarbide (SiOC) interfacial layer, implying covalent bonding between Si and the FG film that is consistent with the mechanical robustness observed from the films. The FG layer is uniform and tunable in thickness and optical transparency by deposition time. Using p-type Si|FG substrates, noncovalent immobilization of cobalt phthalocyanine (CoPc) molecular catalysts was employed for the photoelectrochemical reduction of CO 2 in aqueous solution. The Si|FG|CoPc photocathodes exhibited good catalytic activity, yielding a current density of ∼1 mA/cm 2 , Faradaic efficiency for CO of ∼70% (balance H 2 ), and stable photocurrent for at least 30 h at −1.5 V vs Ag/AgCl under 1-sun illumination. Furthermore, the results suggest that plasma-deposited FG is a robust carbon electrode for molecular catalysts and suitable for further development of aqueous-stable Si photocathodes for CO 2 reduction.

CO2 reduction↗
DOE OSTI2017

Fuzzy Euclidean wormholes in de Sitter space

Here, we investigate Euclidean wormholes in Einstein gravity with a massless scalar field in de Sitter space. Euclidean wormholes are possible due to the analytic continuation of the time as well as complexification of fields, where we need to impose the classicality after the Wick-rotation to the Lorentzian signatures. Furthermore, we prefer wormholes for some parameters, rather than Hawking-Moss instantons, and hence wormholes can be more fundamental than Hawking-Moss type instantons. Euclidean wormholes can be interpreted in three ways: (1) classical big bounce, (2) either tunneling from a small to a large universe or a creation of a collapsing and an expanding universe from nothing, and (3) either a transition from a contracting to a bouncing phase or a creation of two expanding universes from nothing. These various interpretations shed some light on challenges of singularities. In addition, these will help to understand tensions between various kinds of quantum gravity theories.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

A fuzzy logistic regression model based on the least squares estimation

To construct the relationship between fuzzy inputs and fuzzy output described by linguistic variable, we develop a fuzzy logistic regression model, which can be applied for various problems, such as clinical research, risk investment and decision making. In this regard, we introduce the integral calculation of distance of cut sets and a fuzzy adjustment term which could prevent a large fuzzy error for a fuzzy output caused by the output degenerating into crisp number when the independent variables are crisp numbers. The parameters of the fuzzy logistic regression model are derived by means of the least squares method. We adopt three criteria involving mean square error, Kim and Bishu criterion and capability index and also perform two ways of prediction including the in-sample forecast as well as the one-leave-out cross validation. The comparisons with five existing methods show that our proposed method has satisfactory performance and the results are illustrated in some case studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Human attitude analysis based on fuzzy soft differential equations with Bonferroni mean

In this paper, we model a system of fuzzy soft differential equations to analyze the behavior over the time of an individual depending on their companion’s actions under any particular situation against some decision. The Bonferroni mean (BM) is a very useful tool for group decision-making problems when arguments are interrelated to each other as Bonferroni mean can capture the interrelationship of the individual arguments. Using this ability of BM, we define Bonferroni fuzzy soft matrix (BFSM) and weighted Bonferroni fuzzy soft matrix (WBFSM) for data representation. WBFSM is a decision matrix and provide the optimum fuzzy soft constant (OFSC) which is the key element of fuzzy soft differential equation. By utilizing the OFSC, we develop a system of fuzzy soft differential equations to study a dynamical process with nonlinear uncertain and vague data. Second, we present a novel efficient technique for analyzing the future attitude of people due to their present decisions. To illustrate the practicality and feasibility of proposed technique an illustrative example is also discussed with the help of phase portrait and line graphs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

TH-CD-209-04: Fuzzy Robust Optimization in Intensity-Modulated Proton Therapy Planning to Account for Range and Patient Setup Uncertainties

Purpose: We propose to apply a robust optimization model based on fuzzy-logic constraints in the intensity-modulated proton therapy (IMPT) planning subject to range and patient setup uncertainties. The purpose is to ensure the plan robustness under uncertainty and obtain the best trade-off between tumor dose coverage and organ-at-risk(OAR) sparing. Methods: Two IMPT plans were generated for 3 head-and-neck cancer patients: one used the planning target volume(PTV) method; the other used the fuzzy robust optimization method. In the latter method, nine dose distributions were computed - the nominal one and one each for ±3mm setup uncertainties along three cardinal axes and for ±3.5% range uncertainty. For tumors, these nine dose distributions were explicitly controlled by adding hard constraints with adjustable parameters. For OARs, fuzzy constraints that allow the dose to vary within a certain range were used so that the tumor dose distribution was guaranteed by minimum compromise of that of OARs. We rendered this model tractable by converting the fuzzy constraints to linear constraints. The plan quality was evaluated using dose-volume histogram(DVH) indices such as tumor dose coverage(D95%), homogeneity(D5%-D95%), plan robustness(DVH band at D95%), and OAR sparing like D1% of brain and D1% of brainstem. Results: Our model could yield clinically acceptable plans. The fuzzy-logic robust optimization method produced IMPT plans with comparable target dose coverage and homogeneity compared to the PTV method(unit: Gy[RBE]; average[min, max])(CTV D95%: 59 [52.7, 63.5] vs 53.5[46.4, 60.1], CTV D5% - D95%: 11.1[5.3, 18.6] vs 14.4[9.2, 21.5]). It also generated more robust plans(CTV DVH band at D95%: 3.8[1.2, 5.6] vs 11.5[6.2, 16.7]). The parameters of tumor constraints could be adjusted to control the tradeoff between tumor coverage and OAR sparing. Conclusion: The fuzzy-logic robust optimization generates superior IMPT with minimum compromise of OAR sparing. This research was supported by the National Cancer Institute Career Developmental Award K25CA168984, by the Fraternal Order of Eagles Cancer Research Fund Career Development Award, by The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, by Mayo Arizona State University Seed Grant, and by The Kemper Marley Foundation. eRA Person ID(s) for the Principal Investigator: 11017970 (Research Supported by National Institutes of Health)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

A method for classification of red, blue, and green galaxies using fuzzy set theory

ABSTRACT Red and blue galaxies are traditionally classified using some specific cuts in colour or other galaxy properties, which are supported by empirical arguments. The vagueness associated with such cuts are likely to introduce a significant contamination in these samples. Fuzzy sets are vague boundary sets that can efficiently capture the classification uncertainty in the absence of any precise boundary. We propose a method for classification of galaxies according to their colours using fuzzy set theory. We use data from the Sloan Digital Sky Survey (SDSS) to construct a fuzzy set for red galaxies with its members having different degrees of ‘redness’. We show that the fuzzy sets for the blue and green galaxies can be obtained from it using different fuzzy operations. We also explore the possibility of using fuzzy relation to study the relationship between different galaxy properties and discuss its strengths and limitations.

Pandey, Biswajit (ORCID:000000017876595X)↗
DOE OSTI2018

Distance measures for higher order dual hesitant fuzzy sets

In this study, we propose new distance measures for dual hesitant fuzzy sets (DHFSs) in terms of the mean, standard deviation of dual hesitant fuzzy elements (DHFEs), respectively, which overcome some drawbacks of the existing distance measures. Meanwhile, we extend DHFS to its higher order type and refer to it as the higher order dual hesitant fuzzy set (HODHFS). HODHFS is the actual extension of DHFS that enables us to define the membership and non-membership of a given element in terms of several possible generalized type of fuzzy sets (G-Type FSs). The rationale behind HODHFS can be seen in the case that the decision makers are not satisfied by providing exact values for the membership degrees and the non-membership degrees. To indicate HODHFSs have a good performance in decision making, we introduce several distance measures for HODHFSs based on our proposed new distance for dual hesitant fuzzy sets. Finally, we practice our proposed measures for HODHFSs in multi-attribute decision making illustrating their applicability and availability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Optimal Allocation of Water Resources Using a Two-Stage Stochastic Programming Method with Interval and Fuzzy Parameters

Efficient water allocation is one of the most prominent issues in water resources management. In this research, a two-stage interval-parameter stochastic fuzzy programming with type 2 membership functions was used to allocate water resources optimally to different users under uncertainty. This method can handle uncertainties expressed as probability distributions, discrete intervals, and fuzzy sets. The model considers treated wastewater as an allocable water resource in a scenario, in addition to water that is extracted from wellheads, springs, and qanats. Moreover, the loss rate of water during distribution, surplus water in the reservoir in the previous and the next period, and treated wastewater parameters have been incorporated into the model. This model was applied to a case study of water resources allocation within a multi-user and multi-reservoir context in the Zarand region of Kerman, Iran. The results indicate that reasonable solutions have been generated, in the form of interval and fuzzy information under different scenarios that could help managers provide optimal water resources allocation plans. The results also demonstrate that establishing a wastewater treatment station increases the system net benefits, surplus water in wellheads for the next period, and system reliability (level of satisfying the fuzzy goal and constraints), and decreases encountering water shortages.

58 GEOSCIENCES↗
DOE OSTI2019

An Investigation of the Wear Performance of Aged Inconel 718 Superalloy by the Fuzzy Logic Approach

In this study, the effects of δ, γ′ and γ″ phases on the microstructure and wear behavior of Inconel 718 alloy, produced by powder metallurgy technique, were analyzed experimentally and a fuzzy logic model was developed for the weight loss prediction after the wear tests. Aging process was carried out in two stages: firstly at 720 °C for 8 h and then at 620 °C for 6-10 h. Wear tests were performed at five different sliding distances (400-2000 m) for 1 ms{sup −1} sliding speed under 30 to 60 N loads. Weight loss prediction model was developed by using fuzzy logic method. SEM images of Inconel 718 alloy aged for 6, 8 and 10 h at 620 °C show intermetallic precipitates formed around particle boundaries. XRD examinations showed orthorhombic δ (Ni{sub 3}Nb), BCT γ″ (Ni{sub 3}Nb), FCC γ′ Ni{sub 3}(Al,Ti) hexagonal Laves (Fe{sub 2}Nb) phases formed in the structure with the same chemical composition and different crystal lattice. Accurate estimates were obtained in the developed fuzzy logic model. It was illustrated that this fuzzy logic model can be used successfully for the prediction of weight loss in wear tests of Inconel 718 alloy that was produced by powder metallurgy method.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Fuzzy Energy and Reserve Co-optimization With High Penetration of Renewable Energy

In this study, we propose a fuzzy-based energy and reserve co-optimization model with consideration of high penetration of renewable energy. Under the assumption of a fixed uncertainty set of renewables, a two-stage robust model is proposed for clearing energy and reserves in the first stage and checking the feasibility and robustness of re-dispatches in the second stage. Fuzzy sets and their membership functions are introduced into the optimization model to represent the satisfaction degree of the variable uncertainty sets. The lower bound of the uncertainty set is expressed as fuzzy membership functions. The solutions are obtained by transforming the fuzzy mathematical programming formulation into traditional mixed integer linear programming problems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Fault diagnosis and fault tolerant control for T-S fuzzy stochastic distribution systems subject to sensor and actuator faults

The problem of fault diagnosis (FD) and fault tolerant control (FTC) for a class of Takagi-Sugeno (T-S) fuzzy stochastic distribution control (SDC) systems subject to sensor and actuator faults is discussed in this paper. First, fuzzy logic models are used to approximate the output probability density function (PDF). Next, an adaptive augmented state/fault diagnosis observer is proposed to estimate the system state, sensor and the actuator faults simultaneously. New expected weights based on the sensor fault estimation information and a PI-type fuzzy feedback fault tolerant (FT) controller are designed to compensate the effect of sensor fault and actuator fault simultaneously. When the sensor fault occurs, the expected objective is redesigned to compensate the sensor fault. Meanwhile, the PI controller can compensate the effect of actuator fault, and the output PDF of the system can still track the desired PDF after the fault occurs. Finally, an example of quality distribution control in chemical reaction process is given to confirm the effectiveness of the algorithm.

42 ENGINEERING↗
DOE OSTI2018

A novel approach to robust H{sub ∞} integral control for TS fuzzy systems

In this paper, a novel approach to the robust H{sub ∞} integral control for TS fuzzy systems is considered. The control design concept can significantly improve the system stability for such a system. Based on the H{sub ∞} control theory and linear matrix inequality approach, a set of sufficient conditions guarantee the stability of the system and the H{sub ∞} performance. The proposed RHFI controllers are able to work well with the complex nonlinearity and can overcome the effect of approximate rules in the fuzzy system in case of parametric uncertainty existing in the system. This enables the fuzzy system to give appropriate responses with a fewer number of membership functions. Finally, the proposed RHFI controllers are verified through a simulation example, i.e., DFIG wind energy system. The simulated results show that the stability of the system is satisfied and the H{sub ∞} performance is achieved.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Minimax theorems in fuzzy metric spaces

A minimax theorem is a theorem providing conditions which guarantee that the max–min inequality is also an equality. The first theorem in this sense is von Neumann’s minimax theorem, which was considered the starting point of game theory. Since then, several alternative generalizations of von Neumann’s original theorem have appeared in the literature. Variational inequality and minimax problems are of fundamental importance in modern non-linear analysis. They are widely applied in mechanics, differential equations, control theory, mathematical economics, game theory, and optimization. The purpose of this paper is first to establish a minimax theorem for mixed lower–upper semi-continuous functions in fuzzy metric spaces which extends the minimax theorems of many von Neumann types. As applications, we utilize this result to study the existence problems of solutions for abstract variational inequalities and quasi-variational inequalities in fuzzy metric spaces and to study the coincidence problems and saddle problems in fuzzy metric spaces.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

On random fuzzy fractional partial integro-differential equations under Caputo generalized Hukuhara differentiability

This paper is devoted to the study of the solvability of random fuzzy fractional partial integro-differential equations under Caputo generalized Hukuhara differentiability. The notions of random fuzzy variables and fuzzy stochastic processes are developed for multivariable functions. The existence and uniqueness of two types of integral solutions generated from Darboux problem for nonlinear wave equations are proved using the successive approximations method and Gronwall’s inequality for stochastic processes. The continuous dependence on the data, the boundedness, and the stability with probability one of integral solutions are established to confirm the well posedness of our model. Some computational examples are presented to illustrate the theoretical results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

An air quality index-based multistage type-2-fuzzy interval-stochastic programming model for energy and environmental systems management under multiple uncertainties

Highlights: • A multistage type-2-fuzzy interval-stochastic programming (MTIP) method is developed. • Air quality index (AQI) is introduced to manage energy and environmental systems. • AQI-MTIP model is formulated and results for Tianjin's EES are generated. • Impacts of environmental requirements on energy systems is analyzed. • Results can provide support for making effective pollutant mitigation policy. In this study, a multistage type-2-fuzzy interval-stochastic programming (MTIP) method is developed, which extends upon the existing multistage stochastic programming (MSP) by allowing uncertainties expressed as probabilistic distributions, interval values and type-2 fuzzy sets to be effectively incorporated within the optimization framework. Through coupling air quality index (AQI) with MTIP, an AQI-MTIP model is formulated for energy and environmental systems (EES) management of Tianjin. A number of scenarios based on changed AQIs are examined to analyze the impacts of environmental requirements on the city's energy system. Results indicate that (i) with the improvement of environmental requirement, utilization of clean energies (especially natural gas) is provoked markedly; (ii) PM{sub 2.5} is the primary pollutant, 64.50% of which should be reduced each period to maintain the city's air quality at a health-safe level. These findings can help decision makers adjust energy structure, make effective mitigation strategy, and gain deep insight into the relationship between energy consumption and environmental requirement.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Applications of fuzzy logic and best-worst method for tritium sensor selection

Accurate assessment of tritium as a fuel source is critical in fusion reactions, necessitating effective sensor evaluation methods. This study investigates a multi-criteria decision-making framework for selecting tritium sensors, integrating fuzzy logic to enhance decision quality. Initial attempts at applying fuzzy logic were found to be too elementary and failed to capture the complexity of multi-criteria selection; this prompted a refined approach that incorporated expert insights and advanced ranking techniques for sensor evaluation. The research used a two-stage methodology. In the first stage, important criteria and sub-criteria for sensor performance were identified and defined. These criteria were then weighted and scored using a fuzzy best-worst method, drawing upon expert opinions to ensure relevance and validity. The second stage involved interpreting information about varying sensors to rank them based on their overall criteria scores, encouraging the selection of the most suitable options. The result of the study is a proposed method for effective sensor selection in fusion reactors, which in turn will significantly improve the reliability of tritium monitoring in fusion applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗