A branch and bound algorithm for scheduling unit size jobs on parallel batching machines to minimize makespan

In this paper, we present a branch and bound algorithm for the parallel batch scheduling of jobs having different processing times, release dates and unit sizes. There are identical machines with a fixed capacity and the number of jobs in a batch cannot exceed the machine capacity. All batched jobs are processed together and the processing time of a batch is given by the greatest processing time of jobs in that batch. We compare our method to a mixed integer program as well as a method from the literature that is capable of optimally solving instances with a single machine. Computational experiments show that our method is much more efficient than the other two methods in terms of solution time for finding the optimal solution.     

Design of wideband microstrip power divider/combiner with input and output impedance matching for RF energy harvesting applications

Lately, it has been seen that wireless communication systems have been more developed and there has been a huge demand for multi‐spectral transactions. Using circuits for more than one function is a serious requirement in communication technology. Especially, it expected from RF output stages to show the same performance on more than one frequency. To that end, it is required to produce a solution with wideband designs. In this study, a novel power divider/combiner design with a layered conic line has been investigated for the RF energy harvesting applications. The center frequency was set at 2 GHz and concluded with three different designs. In each design, bandwidth and S parameter characteristics were compared according to the number of layers of the transmission, and it was observed that as the number of layers increases, the bandwidth also increases. According to the design result, triple layer Wilkinson power divider was selected to connect to Villard voltage doubler circuit. The Wilkinson power combiner circuit inputs were given between ?10 dBm and 5 dBm input power. As a result, when low input power was given, efficiency was observed about 70%.     

Synthesis of Triblock Copolymers via Photopolymerization of Styrene and Methyl Methacrylate Using Macrophotoinitiators Possessing Poly(ethylene glycol) Units

Macrophotoinitiators based on poly(ethylene glycol)s bearing benzyl tereftalmono amid moieties were synthesized by the reaction of poly(ethylene glycol) (PEG) terminated with terephtaloyl chloride and benzyl amine. The initiators possessing PEG with different molecular weights were used in the photoinduced radical polymerization of styrene (S) and methyl methacrylate (MMA) to yield poly(styrene-b-ethylene glycol-b-styrene) and poly(methyl methacrylate-ethylene glycol-b-methyl methacrylate) triblock copolymers. Characterization of macrophotoinitiators were performed by elemental anlysis, IR and ¹H-NMR spectrum. The elemental analysis results agreed with the theoretical values. The IR and ¹H-NMR spectra showed that the poly(ethylene glycol) units were reacting with the tereftloyl chloride and benzylamine. Characterization of the block copolymers was carried out by spectral measurements, GPC and fractional precipitation methods. The polydispersities of the block copolymers were observed between 1.2–2.32 for poly(methyl methacrylate-ethylene glycol-b-methyl methacrylate) and 1.25–1.90 for poly(styrene-b-ethylene glycol-b-styrene) from GPC measurements.     

MODELING OF 5-AXIS MILLING PROCESSES

5-axis milling operations are common in several industries such as aerospace, automotive and die/mold for machining of sculptured surfaces. In these operations, productivity, dimensional tolerance integrity and surface quality are of utmost importance. Part and tool deflections under high cutting forces may result in unacceptable part quality whereas using conservative cutting parameters results in decreased material removal rate. Process models can be used to determine the proper or optimal milling parameters for required quality with higher productivity. The majority of the existing milling models are for 3-axis operations, even the ones for ball-end mills. In this article, a complete geometry and force model are presented for 5-axis milling operations using ball-end mills. The effect of lead and tilt angles on the process geometry, cutter and workpiece engagement limits, scallop height, and milling forces are analyzed in detail. In addition, tool deflections and form errors are also formulated for 5-axis ball-end milling. The use of the model for selection of the process parameters such as lead and tilt angles that result in minimum cutting forces are also demonstrated. The model predictions for cutting forces and tool deflections are compared and verified by experimental results.     

A systematic design of emulators for multivariable non square and nonlinear systems

In this paper, multimodel and neural emulators are proposed for uncoupled multivariable nonlinear plants with unknown dynamics. The contributions of this paper are to extend the emulators to multivariable non square systems and to propose a systematic method to compute the multimodel synthesis parameters. The effectiveness of the proposed emulators is shown through two simulation examples. The obtained results are very satisfactory, they illustrate the performance of both emulators and show the advantages of the multimodel emulator relatively to the neural one.     

An Application of Genetic Algorithm Search Techniques to the Future Total Exergy Input/Output Estimation

Since 1975, there has been a great deal of interest, particularly during the past decade, in the promising genetic algorithm (GA) and its application to various disciplines from medicine to cogeneration. However, the studies performed on energy-related GA modeling are relatively low in numbers. The main objective of the present study is to develop the exergy input/output estimation equations in order to estimate the future projections based on the GA notion. In this regard, the GA Future Total EXergy Input/Output Estimation Models (GAFTEXIEM/GAFTEXOEM) are used to estimate total exergy input/output demand of Turkey, which is selected as an application country, based on the economic and social indicators of gross domestic product (GDP), population, import, export and house production figures. The future prediction of Turkey's total exergy input/output values are projected between 2003 and 2023. It may be concluded that the models proposed here can be used as an alternative solution and estimation techniques to available estimation techniques. It is also expected that this study will be helpful in developing highly applicable and productive planning for energy policies.     

Thermodynamic performance analysis of a copper–chlorine thermochemical cycle and biomass based combined plant for multigeneration

The primary objective of this work is to investigate a comprehensive thermodynamic assessment of the biomass-assisted multigeneration plant for electrical energy, hydrogen, heating-cooling, drying, and hot water production. The suggested multigeneration plant includes the biomass gasification process, Brayton cycle, Kalina cycle, organic Rankine cycle, and cascade refrigeration plant, which is to produce heating and cooling loads, drying system, hydrogen generation with copper–chlorine thermochemical process, and hydrogen liquefaction process. Based on the thermodynamic laws, the total irreversibility rate and performance assessment of the examined study is conducted. Moreover, the impact of various factors such as reference temperature, biomass gasifier temperature, and mass flow rate of biofuel, on the effectiveness and useful outputs of planned plant are examined. The outcomes of the proposed study show that 18 626, 3948 and 1037 kW electrical energy are generated by using the Brayton, Kalina, and organic Rankine cycle. Furthermore, the total cooling and heating capacities and hydrogen generation rates are 2392, 2864 kW and 0.068 kg s⁻¹. Finally, energetic and exergetic effectiveness of the examined model are calculated as 56.71% and 53.59%.