Seismic safety of lifelines—an optimum design method

Lifeline systems are vulnerable to two types of hazards arising from potential earthquake sources. These are the hazard of a fault-rupture strike on elements of a lifeline system and the hazard of overstress induced in different elements of the system because of the ground vibration. An optimum design method is presented in this paper for the design of a lifeline system for a maximum accepted probability of failure because of any of the two modes of failure. The method may be used to determine an optimum path between a number of fixed points which represent supply or demand stations in the system.     

Sustainable Basin-Scale Water Allocation with Hydrologic State-Dependent Multi-Reservoir Operation Rules

This study extends the PSO-MODSIM model, integrating particle swarm optimization (PSO) algorithm and MODISM river basin decision support system (DSS) to determine optimal basin-scale water allocation, in two aspects. The first is deriving hydrologic state-dependent (conditional) operating rules to better account for drought and high-flow periods, and the second is direct, explicit consideration of sustainability criteria in the model’s formulation to have a better efficiency in basin-scale water allocation. Under conditional operating rules, the operational parameters of reservoir target storage levels and their priority rankings were conditioned on the hydrologic state of the system in a priority-based water allocation scheme. The role of conditional operating rules and policies were evaluated by comparing water shortages associated with objective function values under unconditional and conditional operating rules. Optimal basin-scale water allocation was then evaluated by incorporating reliability, vulnerability, reversibility and equity sustainability indices into the PSO objective function. The extended model was applied for water allocation in the Atrak River Basin, Iran. Results indicated improved distribution of water shortages by about 7.5% using conditional operating rules distinguishing dry, normal and wet hydrologic states. Alternative solutions with nearly identical objective function values were found with sustainability indices included in the model.     

An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions

The world has been challenged since late 2019 by COVID-19. Higher education institutions have faced various challenges in adapting online education to control the pandemic spread of COVID-19. The present study aims to conduct a survey study through the interview and scrutinizing the literature to find the key challenges. Subsequently, an integrated MCDM framework, including Stepwise Weight Assessment Ratio Analysis (SWARA) and Multiple Objective Optimization based on Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), is developed. The SWARA procedure is applied to the analysis and assesses the challenges to adapt the online education during the COVID-19 outbreak, and the MULTIMOORA approach is utilized to rank the higher education institutions on hesitant fuzzy sets. Further, an illustrative case study is considered to express the proposed idea's feasibility and efficacy in real-world decision-making. Finally, the obtained result is compared with other existing approaches, confirming the proposed framework's strength and steadiness. The identified challenges were systemic, pedagogical, and psychological challenges, while the analysis results found that the pedagogical challenges, including the lack of experience and student engagement, were the main essential challenges to adapting online education in higher education institutions during the COVID-19 outbreak.

     

Ranking alternatives in a preferential voting system using fuzzy concepts and data envelopment analysis

In this paper, a new method for aggregating the opinions of experts in a preferential voting system is proposed. The method, which uses fuzzy concept in handling crisp data, is computationally efficient and is able to completely rank the alternatives. Through this method, the number of votes for certain rank position that each alternative receives are first grouped together to form fuzzy numbers. The nearest point to a fuzzy number concept is then used to introduce an artificial ideal alternative. Data envelopment analysis is next used to find the efficiency scores of the alternatives in a pair-wise comparison with the artificial ideal alternative. Alternatives are rank based on these efficiency scores. If the alternatives are not completely ranked, a weight restriction method also based on fuzzy concept is used on the un-discriminated alternatives until they are completely ranked. Two examples are given for illustration of the method.     

Treatability of Alternative Fuel Oxygenates Using Advanced Oxidation, Air Stripping, and Carbon Adsorption

Methyl tert-butyl ether (MTBE) is a gasoline oxygenate that has become a significant threat to groundwater supplies across the United States. Due to its physiochemical properties it has proven difficult and costly to remove from contaminated sites. This study was conducted to determine whether the alternative oxygenates (AO)—diisopropyl ether (DIPE), ethyltert-butyl ether (ETBE), tert-amyl methyl ether (TAME), tert-butyl alcohol (TBA), and ethanol (EtOH)—present a more efficient and less costly option from a remediation standpoint. Air stripping, carbon adsorption, and ultraviolet/H2O2 and O3/H2O2 advanced oxidation processes were examined at pilot scale to develop design parameters from which technical and economic comparisons were made for each alternative oxygenate versus MTBE. The experimental results showed that the ether AOs—DIPE, TAME, and ETBE—were each more efficiently and more economically treated than MTBE. The alternative alcohol oxygenates—TBA and EtOH—were less efficiently and less economically treated by the processes studied. The paper details the effects of primary process parameters and properties of individual oxygenates on process efficiency.     

AZ31-O镁合金和6061-T6铝合金搅拌摩擦焊接头的显微组织和力学性能(英文)

对3 mm厚的AZ31-O镁合金板和6061-T6铝合金板进行异种材料搅拌摩擦焊。实验中搅拌针的旋转速度为600~1400 r/min,前进速度为20~60 mm/min。结果表明,在旋转速度1000 r/min、前进速度40 mm/min的工艺条件下,可以获得无缺陷的焊接接头。组织观察发现搅拌区的晶粒尺寸要比基材区的明显小很多。在搅拌区形成了复杂的金属流动。显微硬度测试表明搅拌区的硬度分别是不均匀的。拉伸实验结果表明,接头的拉伸强度约为基材AZ31镁合金的76%,或6061铝合金的60%。接头拉伸断口SEM形貌观察表明为脆性断裂。     

Optimal power flow of HVDC system using teaching–learning-based optimization algorithm

In this paper, a solution to the optimal power flow (OPF) problem in electrical power networks is presented considering high voltage direct current (HVDC) link. Furthermore, the effect of HVDC link converters on the active and reactive power is evaluated. An objective function is developed for minimizing power loss and improving voltage profile. Gradient-based optimization techniques are not viable due to high number of OPF equations, their complexity and equality and inequality constraints. Hence, an efficient global optimization method is used based on teaching–learning-based optimization (TLBO) algorithm. The performance of the suggested method is evaluated on a 5-bus PJM network and compared with other algorithms such as particle swarm optimization, shuffled frog-leaping algorithm and nonlinear programming. The results are promising and show the effectiveness and robustness of TLBO method.

     

Formulation and Characterization of Human Milk Fat Substitutes Made from Blends of Refined Palm Olein,and Soybean,Olive, Fish,and Virgin Coconut Oils

The simplest and the most cost-effective way of human milk fat substitute (HMFS) production is formulating of suitable vegetable oils at proper ratios. To do this, the D-optimal mixture design was used to optimize the HMFS formulation. The design included 25 formulations made from refined palm olein (35–55%), soybean oil (5–25%), olive oil (5–20%), virgin coconut oil (5–15%), and fish oil (0–10%). Samples were produced in laboratory and characterized in terms of fatty acid and triacylglycerol (TAG) compositions, free fatty acid content, peroxide value, iodine value, and oxidative stability index (OSI). HMFS samples were also compared with Codex Alimentarius (CA) and Iran National Standards Organization (INSO) standards. Each characteristic of HMFS samples was then expressed as a function of ingredient ratio using regression models. Finally, using numerical optimization, four optimized blends (PB₁-PB₄) were selected, made in the laboratory (HMFS₁-HMFS₄), characterized, and compared with CA and INSO standards. The properties of all the optimized blends (except the palmitic acid content of HMFS₂ and the monounsaturated fatty acid [MUFA] content of HMFS₃) met the standards. HMFS₄ showed the highest OSI in Rancimat and the lowest oxidation rate in Schaal oven tests. POL (19.53–21.73%), PPO (20.77–21.73%), OOO (9.11–11.16%), and OPO (8.84–9.46%) were the main (totally about 60%) TAG species found in HMFS samples. In conclusion, the HMFS₄ formula (55% palm olein, 13.5% soybean oil, 16% refined olive oil, 15% virgin coconut oil, and 0.5% fish oil) was suggested as the best formula for HMFS production.     

A Puzzle of Quantum Phase Transition on Gd-IMC by Tuning of Conduction Electron Concentration

Based on the critical unstable of both crystal and magnetic structure of Gd-intermetallic compound near the competition of two strongly independent subsystem （＂local 4f7＂ and ＂conduction electron concentration＂）, a new QPT （quantum point transition） is predicted by calculation of： （1） The band structure and density of state by density functional theory where a strong narrowing fluidity of fermions around EF with shifted to negative value ＂-0.8 eV ＂is observable in the Gd-intermetalliccompound system while in the Y-case, it is not dominated. An antiferromagnetic state on the fluidity of conduction band can be investigated; （2） The internal magnetic field due to short range exchange interaction Jij between the nearest neighbor of local magnetic moment of stable s-state of Gd （L = 0） through the mean field approximation and of Eigenvalue-Eigenfunction ~.（k） are calculated. While a strong negative value of Jy is predicted, the eigenvalue L（k） of the system shows a strong antiferromagnetic phase in the reciprocal lattice direction 〈010〉, 〈001〉 in the correlation length 3.38 ~A. Although the antiferromagnetic state at Rc 〈_ 3.38 °A is a puzzle but it is completely dominated at Rc = 9 °A after passing through the competition between ）.λmin（O） and λmin（π） in the ranger of 3.2 °A 〈 Rc 〈 9 °A. Since both of the antiferromagnetic subsystems are sensitive to the predicted KF, the effect of decreasing of conduction electron is proposed to investigate, the change of the antiferromagnetic ordering state to the competition of ferromagnetic state （in direction 〈010〉） and antiferromagnetic state （in direction 〈001 〉 and 〈 100〉） resulted to paramagnetic state in the long range Rc = 9 °A.     

Multi-objective Phasor Measurement Unit Placement in Electric Power Networks: Integer Linear Programming Formulation

A multi-objective optimal phasor measurement unit placement model using integer linear programming is presented in this article. The proposed model simultaneously optimizes two objectives, i.e., minimization of phasor measurement unit numbers and maximization of measurement redundancy. To calculate the redundancy criteria, the single-line outage and the phasor measurement unit loss are considered simultaneously. A linear formulation is presented for both objective functions. Also herein, to address conflicting attributes and identify Pareto optimal solutions of the multi-objective optimal phasor measurement unit placement problem, a new multi-objective mathematical programming method is proposed. Finally, a new index, i.e., minimum distance to utopia point, is implemented to select the most preferred solution among the available Pareto front based options on the goal to achieve judicious decision makers. Two test systems, i.e., a modified 9-bus and an IEEE 118-bus test systems, are used to illustrate the effectiveness of the proposed framework.