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differential mean value theorem (DMVT) 2

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load and resistance factors 2

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A job-insertion heuristic for minimizing the mean flowtime in dynamic flowshops

Guang GUO, Bo WU, Shuzi YANG

Frontiers of Mechanical Engineering 2011, Volume 6, Issue 2,   Pages 197-202 doi: 10.1007/s11465-011-0211-5

Abstract:

A new adaptive job-insertion based heuristic is presented to minimize the mean flowtime in a dynamicthan the SPT dispatching rule, which is currently one of the most effective methods for minimizing the meanflowtime in dynamic flowshops.

Keywords： scheduling     dynamic flowshops     flowtime     heuristic     mean flowtime    

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Calculations of narrow-band transimissities and the Planck mean absorption coefficients of real gases

Huaqiang CHU, Mingyan GU, Huaichun ZHOU, Fengshan LIU

Frontiers in Energy 2014, Volume 8, Issue 1,   Pages 41-48 doi: 10.1007/s11708-013-0292-4

Abstract: The Planck mean absorption coefficients of CO , H O, CO, and CH in the temperature range of 300 to 2500The SNB model was also used to calculate the Planck mean absorption coefficients of these four radiatingThe LBL results of the Planck mean absorption coefficient were compared with the classical results of

Keywords： transimissity     HITEMP     HITRAN     Planck mean absorption coefficients    

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Theoretical prediction and validation of global horizontal solar irradiance for a tropical climate in India

Sivasankari SUNDARAM,Jakka SARAT CHANDRA BABU

Frontiers in Energy 2015, Volume 9, Issue 3,   Pages 311-321 doi: 10.1007/s11708-015-0369-3

Abstract: The proposed regression models were validated by the significance of statistical indicators such as meanbias error, root mean square error and mean percentage error from the predicted and the actual values

Keywords： global horizontal irradiance (GHI)     mean bias error     root mean square error     mean percentage error     coefficient    

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Some remarks on the engineering application of the fatigue crack growth approach under nonzero mean loads

Jorge Alberto Rodriguez DURAN,Ronney Mancebo BOLOY,Rafael Raider LEONI

Frontiers of Mechanical Engineering 2015, Volume 10, Issue 3,   Pages 255-262 doi: 10.1007/s11465-015-0342-1

Abstract:

The well-known fatigue crack growth (FCG) curves are two-parameter dependents. The range of the stress intensity factor ?K and the load ratio R are the parameters normally used for describing these curves. For engineering purposes, the mathematical representation of these curves should be integrated between the initial and final crack sizes in order to obtain the safety factors for stresses and life. First of all, it is necessary to reduce the dependence of the FCG curves to only one parameter. ?K is almost always selected and, in these conditions, considered as the crack driving force. Using experimental data from literature, the present paper shows how to perform multiple regression analyses using the traditional Walker approach and the more recent unified approach. The correlations so obtained are graphically analyzed in three dimensions. Numerical examples of crack growth analysis for cracks growing under nominal stresses of constant amplitude in smooth and notched geometries are performed, assuming an identical material component as that of the available experimental data. The resulting curves of crack size versus number of cycles (a vs. N) are then compared. The two models give approximately the same (a vs. N) curves in both geometries. Differences between the behaviors of the (avs. N) curves in smooth and notched geometries are highlighted, and the reasons for these particular behaviors are discussed.

Keywords： fatigue crack propagation modeling     life prediction     mean stress effects    

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Observer design for induction motor: an approach based on the mean value theorem

Mohamed Yacine HAMMOUDI,Abdelkarim ALLAG,Mohamed BECHERIF,Mohamed BENBOUZID,Hamza ALLOUI

Frontiers in Energy 2014, Volume 8, Issue 4,   Pages 426-433 doi: 10.1007/s11708-014-0314-x

Abstract: dynamics for the induction motor into the linear parametric varying (LPV) system, the differential mean

Keywords： observer design     differential mean value theorem (DMVT)     sector nonlinearity transformation     linear matrix    

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Mean wind load induced incompatibility in nonlinear aeroelastic simulations of bridge spans

Zhitian ZHANG

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 3,   Pages 605-617 doi: 10.1007/s11709-018-0499-x

Abstract: Mean wind response induced incompatibility and nonlinearity in bridge aerodynamics is discussed, wherethe mean wind and aeroelastic loads are applied simultaneously in time domain.A kind of incompatibility is found during the simultaneous simulation of the mean wind and aeroelasticloads, which leads to incorrect mean wind structural responses.leads to incorrect mean responses due to its nonphysical mean properties.

Keywords： bridge     aerodynamics     nonlinear     aeroelastic model     Pseudo-steady     mean wind loads    

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Classical state feedback controller for nonlinear systems using mean value theorem: closed loop-FOC of

Abrar ALLAG,Abdelhamid BENAKCHA,Meriem ALLAG,Ismail ZEIN,Mohamed Yacine AYAD

Frontiers in Energy 2015, Volume 9, Issue 4,   Pages 413-425 doi: 10.1007/s11708-015-0379-1

Abstract: A simple systematic and useful synthesis method is proposed based on the use of the differential meanThe proposed design approach is based on the mean value theorem (MVT) to express the nonlinear error

Keywords： systems     sector nonlinearity     nonlinear controller     linear matrix inequality (LMI) approach     differential mean    

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Corrigendum to “Multidecadal Trends in Large-Scale Annual Mean SATa Based on CMIP5 Historical Simulations Corrigendum

Nan Xing,Jianping Li,Lanning Wang

Engineering 2017, Volume 3, Issue 3,   Pages 428-428 doi: 10.1016/J.ENG.2017.03.015

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Spatiotemporal evolution and driving factors for GHG emissions of aluminum industry in China

Frontiers in Energy 2023, Volume 17, Issue 2,   Pages 294-305 doi: 10.1007/s11708-022-0819-7

Abstract: China’s aluminum (Al) production has released a huge amount of greenhouse gas (GHG) emissions. As one of the biggest country of primary Al production, China must mitigate its overall GHG emission from its Al industry so that the national carbon neutrality target can be achieved. Under such a background, the study described in this paper conducts a dynamic material flow analysis to reveal the spatiotemporal evolution features of Al flows in China from 2000 to 2020. Decomposition analysis is also performed to uncover the driving factors of GHG emission generated from the Al industry. The major findings include the fact that China’s primary Al production center has transferred to the western region; the primary Al smelting and carbon anode consumption are the most carbon-intensive processes in the Al life cycle; the accumulative GHG emission from electricity accounts for 78.14% of the total GHG emission generated from the Al industry; China’s current Al recycling ratio is low although the corresponding GHG emission can be reduced by 93.73% if all the primary Al can be replaced by secondary Al; and the total GHG emission can be reduced by 88.58% if major primary Al manufacturing firms are transferred from Inner Mongolia to Yunnan. Based upon these findings and considering regional disparity, several policy implications are proposed, including promotion of secondary Al production, support of clean electricity penetration, and relocation of the Al industry.

Keywords： aluminum     material flow analysis     GHG (greenhouse gas) emissions     LMDI (logarithmic mean divisa index    

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Predicting the strength properties of slurry infiltrated fibrous concrete using artificial neural network

T. Chandra Sekhara REDDY

Frontiers of Structural and Civil Engineering 2018, Volume 12, Issue 4,   Pages 490-503 doi: 10.1007/s11709-017-0445-3

Abstract: This paper is aimed at adapting Artificial Neural Networks (ANN) to predict the strength properties of SIFCON containing different minerals admixture. The investigations were done on 84 SIFCON mixes, and specimens were cast and tested after 28 days curing. The obtained experimental data are trained using ANN which consists of 4 input parameters like Percentage of fiber (PF), Aspect Ratio (AR), Type of admixture (TA) and Percentage of admixture (PA). The corresponding output parameters are compressive strength, tensile strength and flexural strength. The predicted values obtained using ANN show a good correlation between the experimental data. The performance of the 4-14-3 architecture was better than other architectures. It is concluded that ANN is a highly powerful tool suitable for assessing the strength characteristics of SIFCON.

Keywords： artificial neural networks     root mean square error     SIFCON     silica fume     metakaolin     steel fiber    

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Probabilistic safety assessment of self-centering steel braced frame

Navid RAHGOZAR, Nima RAHGOZAR, Abdolreza S. MOGHADAM

Frontiers of Structural and Civil Engineering 2018, Volume 12, Issue 1,   Pages 163-182 doi: 10.1007/s11709-017-0384-z

Abstract: Margin of safety, confidence level, and mean annual frequency of the self-centering archetypes for their

Keywords： self-centering steel braced frame     mean annual frequency     safety assessment     confidence level     margin of    

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Weak characteristic information extraction from early fault of wind turbine generator gearbox

Xiaoli XU, Xiuli LIU

Frontiers of Mechanical Engineering 2017, Volume 12, Issue 3,   Pages 357-366 doi: 10.1007/s11465-017-0423-4

Abstract: A weak characteristic information extraction based on µ-SVD and local mean decomposition

Keywords： wind turbine generator gearbox     µ-singular value decomposition     local mean decomposition     weak characteristic    

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Low-carbohydrate diets lead to greater weight loss and better glucose homeostasis than exercise: a randomized clinical trial

Frontiers of Medicine 2021, Volume 15, Issue 3,   Pages 460-471 doi: 10.1007/s11684-021-0861-6

Abstract: Various glycemic parameters, including serum glycated albumin, mean sensor glucose, coefficient of variability

Keywords： low-carbohydrate diet     obesity     nonalcoholic fatty liver disease     continuous glucose monitoring     mean    

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End-of-pipe or process-integrated: evidence from LMDI decomposition of China’s SO

Pingdan ZHANG

Frontiers of Environmental Science & Engineering 2013, Volume 7, Issue 6,   Pages 867-874 doi: 10.1007/s11783-013-0541-0

Abstract: into three parts: source prevention, process control and end-of-pipe treatment, using the Logarithmic Mean

Keywords： end-of-pipe     process-integrated     Logarithmic Mean Divisia Index method (LMDI)     environmental regulation    

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Learning deep IA bidirectional intelligence Personal View

Lei XU

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 4,   Pages 558-562 doi: 10.1631/FITEE.1900541

Abstract: There has been a framework sketched for learning deep bidirectional intelligence. The framework has an inbound that features two actions: one is the acquiring action, which gets inputs in appropriate patterns, and the other is A-S cognition, derived from the abbreviated form of words abstraction and self-organization, which abstracts input patterns into concepts that are labeled and understood by self-organizing parts involved in the concept into structural hierarchies. The top inner domain accommodates relations and a priori knowledge with the help of the A-I thinking action that is responsible for the accumulation-amalgamation and induction-inspiration. The framework also has an outbound that comes with two actions. One is called I-S reasoning, which makes inference and synthesis (I-S) and is responsible for performing various tasks including image thinking and problem solving, and the other is called the interacting action, which controls, communicates with, and inspects the environment. Based on this framework, we further discuss the possibilities of design intelligence through synthesis reasoning.

Keywords： Abstraction     Least mean square error reconstruction (Lmser)     Cognition     Image thinking     Abstract thinking    

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Title Author Date Type Operation

A job-insertion heuristic for minimizing the mean flowtime in dynamic flowshops

Guang GUO, Bo WU, Shuzi YANG

Journal Article

Calculations of narrow-band transimissities and the Planck mean absorption coefficients of real gases

Huaqiang CHU, Mingyan GU, Huaichun ZHOU, Fengshan LIU

Journal Article

Theoretical prediction and validation of global horizontal solar irradiance for a tropical climate in India

Sivasankari SUNDARAM,Jakka SARAT CHANDRA BABU

Journal Article

Some remarks on the engineering application of the fatigue crack growth approach under nonzero mean loads

Jorge Alberto Rodriguez DURAN,Ronney Mancebo BOLOY,Rafael Raider LEONI

Journal Article

Observer design for induction motor: an approach based on the mean value theorem

Mohamed Yacine HAMMOUDI,Abdelkarim ALLAG,Mohamed BECHERIF,Mohamed BENBOUZID,Hamza ALLOUI

Journal Article

Mean wind load induced incompatibility in nonlinear aeroelastic simulations of bridge spans

Zhitian ZHANG

Journal Article

Classical state feedback controller for nonlinear systems using mean value theorem: closed loop-FOC of

Abrar ALLAG,Abdelhamid BENAKCHA,Meriem ALLAG,Ismail ZEIN,Mohamed Yacine AYAD

Journal Article

Corrigendum to “Multidecadal Trends in Large-Scale Annual Mean SATa Based on CMIP5 Historical Simulations

Nan Xing,Jianping Li,Lanning Wang

Journal Article

Spatiotemporal evolution and driving factors for GHG emissions of aluminum industry in China

Journal Article

Predicting the strength properties of slurry infiltrated fibrous concrete using artificial neural network

T. Chandra Sekhara REDDY

Journal Article

Probabilistic safety assessment of self-centering steel braced frame

Navid RAHGOZAR, Nima RAHGOZAR, Abdolreza S. MOGHADAM

Journal Article

Weak characteristic information extraction from early fault of wind turbine generator gearbox

Xiaoli XU, Xiuli LIU

Journal Article

Low-carbohydrate diets lead to greater weight loss and better glucose homeostasis than exercise: a randomized clinical trial

Journal Article

End-of-pipe or process-integrated: evidence from LMDI decomposition of China’s SO

Pingdan ZHANG

Journal Article

Learning deep IA bidirectional intelligence

Lei XU

Journal Article