scholarly journals Evaluation and Multi-Objective Optimization of Lightweight Mortars Parameters at Elevated Temperature via Box–Behnken Optimization Approach

Materials ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7405
Author(s):  
Mehmet Kaya ◽  
Zeynel Baran Yıldırım ◽  
Fuat Köksal ◽  
Ahmet Beycioğlu ◽  
Izabela Kasprzyk
Keyword(s):  
Mechanical Properties ◽  
Compressive Strength ◽  
Silica Fume ◽  
P Value ◽  
Model Parameters ◽  
Powder Materials ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Critical Temperatures ◽  
Multi Objective

In this research, the mechanical properties of lightweight mortars containing different percentages of additional powder materials has been investigated using response surface methodology (RSM). Box–Behnken design, one of the RSM techniques, was used to study the effects of silica fume content (5, 10, and 15%), vermiculite/cement (V/C) ratio (4, 6, and 8), and temperature (300, 600, and 900 °C) on the ultrasonic pulse velocity (UPV), bending strength, and compressive strength of lightweight mortars. Design expert statistical software was accustomed to determining and evaluating the mix-design of materials in mortar mixtures and temperature effect on mortars. After preliminary experimental research of the relationships between independent and response variables, regression models were built. During the selection of the model parameters, F value, p-value, and R2 values of the statistical models were taken into account by using the backward elimination technique. The results showed a high correlation between the variables and responses. Multi-objective optimization results showed that the critical temperatures for different levels of silica fume (5–10–15%) were obtained as 371.6 °C, 306.3 °C, and 436 °C, respectively, when the V/C ratio kept constant as 4. According to the results obtained at high desirability levels, it is found that the UPS values varied in the range of 2480–2737 m/s, flexural strength of 3.13–3.81 MPa, and compressive strength of 9.9–11.5 MPa at these critical temperatures. As a result of this research, RSM is highly recommended to evaluate mechanical properties where concrete includes some additional powder materials and was exposed to high temperature.

scholarly journals The Influence of the Use of Cement Brands on the Physical and Mechanical Properties of Reactive Powder Concrete (RPC)

2021 ◽  
Vol 2 (4) ◽  
Author(s):  
E. Sutandar ◽  
Setya Budi ◽  
F. Juniardi
Keyword(s):  
Mechanical Properties ◽  
Compressive Strength ◽  
Silica Fume ◽  
Binding Capacity ◽  
Physical And Mechanical Properties ◽  
Reactive Powder Concrete ◽  
Powder Materials ◽  
Fine Aggregate ◽  
Reactive Material ◽  
Reactive Powder

The most popular building material today is concrete. Concrete is used for buildings, industrial structures, bridges, railroad sleepers, roads, dams and more. Along with the development of concrete technology is increasingly developing and innovative so as to achieve better characteristics, cheaper prices and environmentally friendly. In the early days of the development of concrete it is explained to us about the origin from ancient times to civilization to the present century of its development. In current developments, concrete already has a very high compressive strength up to 200-800 MPa, this is also called Ultra Hight Concrete (UHC). It is developed by the Reactive Powder concrete (RPC) method. Where in the research conducted, the manufacture of reactive material, namely Reactive Powder concrete (RPC) was given with a compressive strength of up to 52 MPa. The components of the RPC mixture consist of cement, fine aggregate, silica fume, superplasticizer and water. To produce a compressive strength of 52 MPa, the composition of the mixture used previous research. Detailed RPC concrete mix proportions are given in this study. Preparation and testing of materials are made in the laboratory of the Faculty of Civil Engineering in Untan. The results that will be obtained are the physical and mechanical properties of RPC Concrete. As previously explained, the manufacture of RPC concrete requires basic ingredients that include cement, fine aggregate, silica fume, superplasticizer and water mixed together. Of course, with basic ingredients with good and correct composition, the physical and mechanical properties of RPC concrete will reach the planned quality. Cement sold in the market today has PPC and PCC types. Therefore, the cement which is a binder of powder materials into a solid one plays a very important role in the formation of the best physical and mechanical properties of RPC concrete. With cement as a binding material, it is certain that the strength of RPC concrete is determined by the binding capacity of the type of cement to be used, thus RPC concrete will be obtained according to the planned quality of the plan. From the cement brands on the Indonesian market consisting of PPC and PCC cement types, it can be concluded that one of the cements using the PCC type cement brand has better physical and mechanical properties than the PPC type cement brand. And all brands of cement with PCC type produce compressive strength > 52 MPa. So, in the manufacture of RPC concrete it is recommended to use a cement brand with PCC type.

scholarly journals A New Approach to Group Multi-Objective Optimization under Imperfect Information and Its Application to Project Portfolio Optimization

2021 ◽  
Vol 11 (10) ◽  
pp. 4575
Author(s):  
Eduardo Fernández ◽  
Nelson Rangel-Valdez ◽  
Laura Cruz-Reyes ◽  
Claudia Gomez-Santillan
Keyword(s):  
Portfolio Optimization ◽  
Imperfect Information ◽  
Model Parameters ◽  
Final Decision ◽  
Project Portfolio ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
New Approach ◽  
Multi Objective ◽  
Group Member

This paper addresses group multi-objective optimization under a new perspective. For each point in the feasible decision set, satisfaction or dissatisfaction from each group member is determined by a multi-criteria ordinal classification approach, based on comparing solutions with a limiting boundary between classes “unsatisfactory” and “satisfactory”. The whole group satisfaction can be maximized, finding solutions as close as possible to the ideal consensus. The group moderator is in charge of making the final decision, finding the best compromise between the collective satisfaction and dissatisfaction. Imperfect information on values of objective functions, required and available resources, and decision model parameters are handled by using interval numbers. Two different kinds of multi-criteria decision models are considered: (i) an interval outranking approach and (ii) an interval weighted-sum value function. The proposal is more general than other approaches to group multi-objective optimization since (a) some (even all) objective values may be not the same for different DMs; (b) each group member may consider their own set of objective functions and constraints; (c) objective values may be imprecise or uncertain; (d) imperfect information on resources availability and requirements may be handled; (e) each group member may have their own perception about the availability of resources and the requirement of resources per activity. An important application of the new approach is collective multi-objective project portfolio optimization. This is illustrated by solving a real size group many-objective project portfolio optimization problem using evolutionary computation tools.

scholarly journals Multi-Objective Multidisciplinary Design Optimization of a Robotic Fish System

2021 ◽  
Vol 9 (5) ◽  
pp. 478
Author(s):  
Hao Chen ◽  
Weikun Li ◽  
Weicheng Cui ◽  
Ping Yang ◽  
Linke Chen
Keyword(s):  
Design Optimization ◽  
Optimization Algorithm ◽  
Multidisciplinary Design Optimization ◽  
Robotic Fish ◽  
Multidisciplinary Design ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cfd Method ◽  
The Individual

Biomimetic robotic fish systems have attracted huge attention due to the advantages of flexibility and adaptability. They are typically complex systems that involve many disciplines. The design of robotic fish is a multi-objective multidisciplinary design optimization problem. However, the research on the design optimization of robotic fish is rare. In this paper, by combining an efficient multidisciplinary design optimization approach and a novel multi-objective optimization algorithm, a multi-objective multidisciplinary design optimization (MMDO) strategy named IDF-DMOEOA is proposed for the conceptual design of a three-joint robotic fish system. In the proposed IDF-DMOEOA strategy, the individual discipline feasible (IDF) approach is adopted. A novel multi-objective optimization algorithm, disruption-based multi-objective equilibrium optimization algorithm (DMOEOA), is utilized as the optimizer. The proposed MMDO strategy is first applied to the design optimization of the robotic fish system, and the robotic fish system is decomposed into four disciplines: hydrodynamics, propulsion, weight and equilibrium, and energy. The computational fluid dynamics (CFD) method is employed to predict the robotic fish’s hydrodynamics characteristics, and the backpropagation neural network is adopted as the surrogate model to reduce the CFD method’s computational expense. The optimization results indicate that the optimized robotic fish shows better performance than the initial design, proving the proposed IDF-DMOEOA strategy’s effectiveness.

scholarly journals Mechanical properties optimization of the steering column based on multi-objective optimization design

2016 ◽  
Vol 8 (12) ◽  
pp. 168781401668294 ◽  
Author(s):  
Si Chen ◽  
Zhaohui Wang ◽  
Mi Lv
Keyword(s):  
Mechanical Properties ◽  
Process Parameters ◽  
Optimization Design ◽  
Strain Difference ◽  
Optimization Method ◽  
Equivalent Strain ◽  
Multi Objective Optimization ◽  
Optimal Process ◽  
Multi Objective ◽  
Initial Results

The mechanical properties of the steering column have a significant influence on the comfort and stability of a vehicle. In order for the mechanical properties to be improved, the rotary swaging process of the steering column is studied in this article. The process parameters, including axial feed rate, hammerhead speed, and hammerhead radial reduction, are systematically analyzed and optimized based on a multi-objective optimization design. The response surface methodology and the genetic algorithm are employed for optimal process parameters to be obtained. The maximum damage value, the maximum forming load, and the equivalent strain difference obtained with the optimal process parameters are, respectively, decreased by 30.09%, 7.44%, and 57.29% compared to the initial results. The comparative results present that the quality of the steering column is improved. The torque experiments and fatigue experiments are conducted with the optimal steering column. The maximum torque is measured to be 260 NM, and the service life is measured to be 2 weeks (40 NM, 2500 times), which are, respectively, increased by 8.3% and 8.69% compared to the initial results. The above results display that the mechanical properties of the steering column are optimized to verify the feasibility of the multi-objective optimization method.

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