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Robust topology optimization of multi-material lattice structures under material and load uncertainties

Yu-Chin CHAN, Kohei SHINTANI, Wei CHEN

Frontiers of Mechanical Engineering 2019, Volume 14, Issue 2,   Pages 141-152 doi: 10.1007/s11465-019-0531-4

Abstract: Enabled by advancements in multi-material additive manufacturing, lightweight lattice structures consistinglattice structures under any combination of material and load uncertainties.The method utilizes a new generalized material interpolation scheme for an arbitrary number of materials, and employs univariate dimension reduction and Gauss-type quadrature to quantify and propagate uncertaintyExamples of a cantilever beam lattice structure under various material and load uncertainty cases exhibit

Keywords： robust topology optimization     lattice structures     multi-material     material uncertainty     load uncertainty    

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Robust topology optimization of hinge-free compliant mechanisms with material uncertainties based on

Junjie ZHAN, Yangjun LUO

Frontiers of Mechanical Engineering 2019, Volume 14, Issue 2,   Pages 201-212 doi: 10.1007/s11465-019-0529-y

Abstract: new robust topology optimization framework for hinge-free compliant mechanisms with spatially varying materialminimize the variation in output displacement under constraints of the mean displacement and predefined material

Keywords： compliant mechanisms     robust topology optimization     hinges     uncertainty     bounded field    

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Managing obsolescence of embedded hardware and software in secure and trusted systems

Zachary A. COLLIER, James H. LAMBERT

Frontiers of Engineering Management 2020, Volume 7, Issue 2,   Pages 172-181 doi: 10.1007/s42524-019-0032-5

Abstract: Obsolescence of integrated systems which contain hardware and software is a problem that affects multiple industries and can occur for many reasons, including technological, economic, organizational, and social factors. It is especially acute in products and systems that have long life cycles, where a high rate of technological innovation of the subcomponents result in a mismatch in life cycles between the components and the systems. While several approaches for obsolescence forecasting exist, they often require data that may not be available. This paper describes an approach using non-probabilistic scenarios coupled with decision analysis to investigate how particular scenarios influence priority setting for products and systems. Scenarios are generated from a list of emergent and future conditions related to obsolescence. The key result is an identification of the most and least disruptive scenarios to the decision maker’s priorities. An example is presented related to the selection of technologies for energy islanding, which demonstrates the methodology using six obsolescence scenarios. The paper should be of broad interest to scholars and practitioners engaged with enterprise risk management and similar challenges of large-scale systems.

Keywords： enterprise risk management     diminishing manufacturing sources and material shortages     scenario-based preferences     systems engineering     deep uncertainty     product life cycle    

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Modeling the impact of uncertainty in emissions trading markets with bankable permits

Yongliang ZHANG, Bing ZHANG, Jun BI, Pan HE

Frontiers of Environmental Science & Engineering 2013, Volume 7, Issue 2,   Pages 231-241 doi: 10.1007/s11783-012-0431-x

Abstract: The various forms of uncertainty that firms may face in bankable emission permit trading markets willThis research explores the effect of increased uncertainty over future input costs and output pricesIncreased uncertainty about future market conditions increases the expected permit price and causes aFinally, safety valves, both low-side and high-side, are suggested to reduce the impact of uncertainty

Keywords： uncertainty     bankable     emission trading     market performance    

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Key uncertainty events impacting on the completion time of highway construction projects

Alireza MOGHAYEDI, Abimbola WINDAPO

Frontiers of Engineering Management 2019, Volume 6, Issue 2,   Pages 275-298 doi: 10.1007/s42524-019-0022-7

Abstract: This paper examines the uncertainty events encountered in the process of constructing highways, and evaluatesThe research made use of a review of extant literature in the area of uncertainty management, and modelingAn uncertainty matrix for South African highway projects was developed, using a quantitative model andIt emerged from the study that the uncertainty events affecting the construction time of highway projectstime differently, through a combination of the uncertainty events of the individual construction activities

Keywords： ANFIS     construction time     impact assessment     highway project     South Africa     uncertainty    

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Comprehensive Discussion on the Extension of Generalized Uncertainty Systems Theory

Wang Qingyin,Lii Ruihua

Strategic Study of CAE 2005, Volume 7, Issue 10,   Pages 16-22

Abstract:

Based on comprehensive discussion on the connotation of generalized uncertainty systems theory, thispaper discusses the extension of generalized uncertainty systems theory as well as the basic frame andIt is a base to study generalized uncertainty systems theory.

Keywords： generalized uncertainty information     uncertainty mathematics     generalized uncertainty systems theory    

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Uncertainty of concrete strength in shear and flexural behavior of beams using lattice modeling

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 2,   Pages 306-325 doi: 10.1007/s11709-022-0890-5

Abstract: This paper numerically studied the effect of uncertainty and random distribution of concrete strengthThree levels of material deficiency (i.e., 10%, 20%, 30%) were randomly introduced to 5%, 10%, 15%, andCapability of lattice modeling was highlighted as an efficient tool to account for uncertainty in statistical

Keywords： lattice modeling     shear failure     flexural failure     uncertainty     deficiency     numerical simulation    

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Evaluation of measurement uncertainty of the high-speed variable-slit system based on the Monte Carlo

Yin ZHANG, Jianwei WU, Kunpeng XING, Zhongpu WEN, Jiubin TAN

Frontiers of Mechanical Engineering 2020, Volume 15, Issue 4,   Pages 517-537 doi: 10.1007/s11465-020-0589-z

Abstract: This paper presents a dynamic and static error transfer model and uncertainty evaluation method for aFinally, the uncertainty of the blade displacement measurement is evaluated using the Monte Carlo method

Keywords： air-floating guide rail     error transfer model     driving and following structure     dynamic error     uncertainty    

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Liquid metal material genome: Initiation of a new research track towards discovery of advanced energy

Lei WANG, Jing LIU

Frontiers in Energy 2013, Volume 7, Issue 3,   Pages 317-332 doi: 10.1007/s11708-013-0271-9

Abstract: With many superior physical properties over conventional fluids, the low melting point liquid metal materialInspired by the Material Genome Initiative as issued in 2011 by the United States of America, a morespecific and focused project initiative was proposed in this paper—the liquid metal material genome aimedThe theoretical strategies and experimental methods in the research and development of liquid metal materialParticularly, the calculation of phase diagram (CALPHAD) approach as a highly effective way for material

Keywords： liquid metal material genome     energy material     material discovery     advanced material     room-temperature liquid    

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temperature in automotive engines over coldstart operation in the presence of different random noises and uncertainty

Nasser L. AZAD,Ahmad MOZAFFARI

Frontiers of Mechanical Engineering 2015, Volume 10, Issue 4,   Pages 405-412 doi: 10.1007/s11465-015-0354-x

Abstract: main scope of the current study is to develop a systematic stochastic model to capture the undesired uncertaintyHowever, there exist rare reports which propose an efficient tool for coping with the uncertainty associated

Keywords： automotive engine     calibration     coldstart operation     Gaussian process regression machine (GPRM)     uncertainty    

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The Argument Foundation of Generalized Uncertainty Systems Theory

Wang Qingyin,Guo Litian,Xie Jianhua,Liu Zhiyong

Strategic Study of CAE 2004, Volume 6, Issue 3,   Pages 25-29

Abstract:

The paper discusses the brief development of uncertainty system theory at home and abroad, gives thedefinition of uncertainty systems, and presents the basic conception, basic structure, argument foundation

Keywords： uncertainty information     generalized uncertainty system     basic structure    

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Probabilistic seismic response and uncertainty analysis of continuous bridges under near-fault ground

Hai-Bin MA, Wei-Dong ZHUO, Davide LAVORATO, Camillo NUTI, Gabriele FIORENTINO, Giuseppe Carlo MARANO, Rita GRECO, Bruno BRISEGHELLA

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 6,   Pages 1510-1519 doi: 10.1007/s11709-019-0577-8

Abstract: On this basis, the uncertainty analysis is conducted with the key sources of uncertainty during the finiteAll the results are quantified by the “swing” base on the specific distribution range of each uncertaintyprobabilistic seismic demand model; damping ratio, pier diameter and concrete strength are the main uncertainty

Keywords： continuous bridge     probabilistic seismic demand model     Intensity Measure     near-fault     uncertainty    

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An integrated optimization and simulation approach for air pollution control under uncertainty in open-pit

Zunaira Asif, Zhi Chen

Frontiers of Environmental Science & Engineering 2019, Volume 13, Issue 5, doi: 10.1007/s11783-019-1156-x

Abstract: Air Pollution Control model is developed for open-pit metal mines. Model will aid decision makers to select a cost-effective solution. Open-pit metal mines contribute toward air pollution and without effective control techniques manifests the risk of violation of environmental guidelines. This paper establishes a stochastic approach to conceptualize the air pollution control model to attain a sustainable solution. The model is formulated for decision makers to select the least costly treatment method using linear programming with a defined objective function and multi-constraints. Furthermore, an integrated fuzzy based risk assessment approach is applied to examine uncertainties and evaluate an ambient air quality systematically. The applicability of the optimized model is explored through an open-pit metal mine case study, in North America. This method also incorporates the meteorological data as input to accommodate the local conditions. The uncertainties in the inputs, and predicted concentration are accomplished by probabilistic analysis using Monte Carlo simulation method. The output results are obtained to select the cost-effective pollution control technologies for PM2.5, PM10, NOx, SO2 and greenhouse gases. The risk level is divided into three types (loose, medium and strict) using a triangular fuzzy membership approach based on different environmental guidelines. Fuzzy logic is then used to identify environmental risk through stochastic simulated cumulative distribution functions of pollutant concentration. Thus, an integrated modeling approach can be used as a decision tool for decision makers to select the cost-effective technology to control air pollution.

Keywords： Air pollution     Decision analysis     Linear programming     Mining     Optimization     Fuzzy     Monte Carlo    

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Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents

Jiping Jiang, Feng Han, Yi Zheng, Nannan Wang, Yixing Yuan

Frontiers of Environmental Science & Engineering 2018, Volume 12, Issue 5, doi: 10.1007/s11783-018-1081-4

Abstract:

Uncertainty rules of pollution source inversion are revealed by stochastic>

A release load is most easily inversed and source locations own largest uncertainty/p>

Instantaneous spill assumption has much less uncertainty

Keywords： River chemical spills     Emergency response     Pollution source inversion     Inverse uncertainty analysis     Regional    

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Uncertainty in Knowledge Representation

Li Deyi

Strategic Study of CAE 2000, Volume 2, Issue 10,   Pages 73-79

Abstract: And the difficulty is uncertainty hidden in qualitative concepts, that is the randomness and fuzziness

Keywords： knowledge representation     qualitative concept     uncertainty     cloud model     digital characteristics    

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Title Author Date Type Operation

Robust topology optimization of multi-material lattice structures under material and load uncertainties

Yu-Chin CHAN, Kohei SHINTANI, Wei CHEN

Journal Article

Robust topology optimization of hinge-free compliant mechanisms with material uncertainties based on

Junjie ZHAN, Yangjun LUO

Journal Article

Managing obsolescence of embedded hardware and software in secure and trusted systems

Zachary A. COLLIER, James H. LAMBERT

Journal Article

Modeling the impact of uncertainty in emissions trading markets with bankable permits

Yongliang ZHANG, Bing ZHANG, Jun BI, Pan HE

Journal Article

Key uncertainty events impacting on the completion time of highway construction projects

Alireza MOGHAYEDI, Abimbola WINDAPO

Journal Article

Comprehensive Discussion on the Extension of Generalized Uncertainty Systems Theory

Wang Qingyin,Lii Ruihua

Journal Article

Uncertainty of concrete strength in shear and flexural behavior of beams using lattice modeling

Journal Article

Evaluation of measurement uncertainty of the high-speed variable-slit system based on the Monte Carlo

Yin ZHANG, Jianwei WU, Kunpeng XING, Zhongpu WEN, Jiubin TAN

Journal Article

Liquid metal material genome: Initiation of a new research track towards discovery of advanced energy

Lei WANG, Jing LIU

Journal Article

temperature in automotive engines over coldstart operation in the presence of different random noises and uncertainty

Nasser L. AZAD,Ahmad MOZAFFARI

Journal Article

The Argument Foundation of Generalized Uncertainty Systems Theory

Wang Qingyin,Guo Litian,Xie Jianhua,Liu Zhiyong

Journal Article

Probabilistic seismic response and uncertainty analysis of continuous bridges under near-fault ground

Hai-Bin MA, Wei-Dong ZHUO, Davide LAVORATO, Camillo NUTI, Gabriele FIORENTINO, Giuseppe Carlo MARANO, Rita GRECO, Bruno BRISEGHELLA

Journal Article

An integrated optimization and simulation approach for air pollution control under uncertainty in open-pit

Zunaira Asif, Zhi Chen

Journal Article

Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents

Jiping Jiang, Feng Han, Yi Zheng, Nannan Wang, Yixing Yuan

Journal Article

Uncertainty in Knowledge Representation

Li Deyi

Journal Article