Optimization of Wind-Up Tension of Webs Preventing Wrinkles and Slippage

Author(s):  
Hiromu Hashimoto

This paper describes the optimization method of wind-up tension to prevent wound roll defects, mainly star defects and slippage, based on the optimum design technique. Hakiel’s nonlinear model with air entrainment effects is applied to analyze in-roll stress distributions in the radial and tangential directions (1987, “Nonlinear Model for Wound Roll Stresses,” Tappi J., 70(5), pp. 113–117). It is well known experimentally that a decrease in the wind-up tension prevents star defects due to negative tangential stress under winding. Thus, in the present optimization method, wind-up tension is gradually decreased in the radial direction to minimize the averaged value of tangential stresses under the constraint of non-negative tangential stresses. Furthermore, the relation of the slippage between wound film layers and in-roll stress of a roll is considered. Successive quadratic programming, which is the typical mathematical programming method, is used as the optimization technique. Wind-up tension is expressed by the third-order spline curve of a radial coordinate. The liner function with respect to the radial coordinate is used as the original wind-up tension. The optimized wind-up tensions are obtained for various winding conditions, and we confirmed that the in-roll stress distributions were very much improved for preventing wrinkles and slippage by the optimization method proposed.

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4649
Author(s):  
İsmail Hakkı ÇAVDAR ◽  
Vahit FERYAD

One of the basic conditions for the successful implementation of energy demand-side management (EDM) in smart grids is the monitoring of different loads with an electrical load monitoring system. Energy and sustainability concerns present a multitude of issues that can be addressed using approaches of data mining and machine learning. However, resolving such problems due to the lack of publicly available datasets is cumbersome. In this study, we first designed an efficient energy disaggregation (ED) model and evaluated it on the basis of publicly available benchmark data from the Residential Energy Disaggregation Dataset (REDD), and then we aimed to advance ED research in smart grids using the Turkey Electrical Appliances Dataset (TEAD) containing household electricity usage data. In addition, the TEAD was evaluated using the proposed ED model tested with benchmark REDD data. The Internet of things (IoT) architecture with sensors and Node-Red software installations were established to collect data in the research. In the context of smart metering, a nonintrusive load monitoring (NILM) model was designed to classify household appliances according to TEAD data. A highly accurate supervised ED is introduced, which was designed to raise awareness to customers and generate feedback by demand without the need for smart sensors. It is also cost-effective, maintainable, and easy to install, it does not require much space, and it can be trained to monitor multiple devices. We propose an efficient BERT-NILM tuned by new adaptive gradient descent with exponential long-term memory (Adax), using a deep learning (DL) architecture based on bidirectional encoder representations from transformers (BERT). In this paper, an improved training function was designed specifically for tuning of NILM neural networks. We adapted the Adax optimization technique to the ED field and learned the sequence-to-sequence patterns. With the updated training function, BERT-NILM outperformed state-of-the-art adaptive moment estimation (Adam) optimization across various metrics on REDD datasets; lastly, we evaluated the TEAD dataset using BERT-NILM training.


Author(s):  
Patrick Nwafor ◽  
Kelani Bello

A Well placement is a well-known technique in the oil and gas industry for production optimization and are generally classified into local and global methods. The use of simulation software often deployed under the direct optimization technique called global method. The production optimization of L-X field which is at primary recovery stage having five producing wells was the focus of this work. The attempt was to optimize L-X field using a well placement technique.The local methods are generally very efficient and require only a few forward simulations but can get stuck in a local optimal solution. The global methods avoid this problem but require many forward simulations. With the availability of simulator software, such problem can be reduced thus using the direct optimization method. After optimization an increase in recovery factor of over 20% was achieved. The results provided an improvement when compared with other existing methods from the literatures.


2016 ◽  
Vol 49 (1) ◽  
pp. 182-187 ◽  
Author(s):  
J. Todt ◽  
H. Hammer ◽  
B. Sartory ◽  
M. Burghammer ◽  
J. Kraft ◽  
...  

Synchrotron X-ray nanodiffraction is used to analyse residual stress distributions in a 200 nm-thick W film deposited on the scalloped inner wall of a through-silicon via. The diffraction data are evaluated using a novel dedicated methodology which allows the quantification of axial and tangential stress components under the condition that radial stresses are negligible. The results reveal oscillatory axial stresses in the range of ∼445–885 MPa, with a distribution that correlates well with the scallop wavelength and morphology, as well as nearly constant tangential stresses of ∼800 MPa. The discrepancy with larger stress values obtained from a finite-element model, as well as from a blanket W film, is attributed to the morphology and microstructural nature of the W film in the via.


Author(s):  
Dhaval Desai ◽  
Jiang Zhou

In a world where the increasing demand on developing energy-efficient systems is probably the most stringent design constraint, the trend in engineering research in recent years has been to optimize the existing technologies rather than to implement new ones. The present work addresses a robust axial-type fan design technique developed using an optimization technique. A fan is indispensable equipment for primary and local ventilation in mining industries. We always pursue the fan with high working efficiency and low noise. In this paper, an optimization method is developed to improve the pneumatic properties of the fan based on the blade element theory. A new type of fan used in local ventilation is designed with the help of computer. It is shown that the new design enhanced the efficient up to 88%. Numerical analysis is also conducted to validate the optimization design results.


2021 ◽  
Vol 30 (2) ◽  
pp. 354-364
Author(s):  
Firas Al-Mashhadani ◽  
Ibrahim Al-Jadir ◽  
Qusay Alsaffar

In this paper, this method is intended to improve the optimization of the classification problem in machine learning. The EKH as a global search optimization method, it allocates the best representation of the solution (krill individual) whereas it uses the simulated annealing (SA) to modify the generated krill individuals (each individual represents a set of bits). The test results showed that the KH outperformed other methods using the external and internal evaluation measures.


2021 ◽  
Author(s):  
Jonas Berlin ◽  
Georg Hess ◽  
Anton Karlsson ◽  
William Ljungbergh ◽  
Ze Zhang ◽  
...  

This paper presents an approach to collision-free, long-range trajectory generation for a mobile robot in an industrial environment with static and dynamic obstacles. For the long range planning a visibility graph together with A* is used to find a collision-free path with respect to the static obstacles. This path is used as a reference path to the trajectory planning algorithm that in addition handles dynamic obstacles while complying with the robot dynamics and constraints. A Nonlinear Model Predictive Control (NMPC) solver generates a collision-free trajectory by staying close the initial path but at the same time obeying all constraints. The NMPC problem is solved efficiently by leveraging the new numerical optimization method Proximal Averaged Newton for Optimal Control (PANOC). The algorithm was evaluated by simulation in various environments and successfully generated feasible trajectories spanning hundreds of meters in a tractable time frame.


2021 ◽  
Author(s):  
Ramyar Rashed Mohassel

With the introduction of new technologies, concepts and approaches in power transmission, distribution and utilization such as Smart Grids (SG), Advanced Metering Infrastructures (AMI), Distributed Energy Resources (DER) and Demand Side Management (DSM), new capabilities have emerged that enable efficient use and management of power consumption. These capabilities are applicable at micro level in households and building complexes as well as at macro level for utility providers in form of resource and revenue management initiatives. On the other hand, integration of Information Technology (IT) and instrumentation has brought Building Management Systems (BMS) to our homes and has made it possible for the ordinary users to take advantage of more complex and sophisticated energy and cost management features as an integral part of their BMS. The idea of combining capabilities and advantages offered by SG, AMI, DER, DSM and BMS is the backbone of this thesis and has resulted in developing a unique, two-level optimization method for effective deployment of DSM at households and residential neighborhoods. The work consists of an optimization algorithm for households to maximize utilization of DER as the lower level of the envisioned two-level optimization technique while using a customized Game Theoretic optimization for optimizing revenue of utility providers for residential neighborhood as the upper level. This work will also introduce a power management unit, called Load Moderation Center (LMC), to host the developed optimization algorithms as an integrated part of BMS. LMC, upon successful completion, will be able to automatically plan consumption, effectively utilize available sources including grid, renewable energies and storages, and eliminate the need for residences to manually program their BMS for different market scenarios.


2021 ◽  
Vol 850 (1) ◽  
pp. 012017
Author(s):  
J Shri Saranyaa ◽  
A Peer Fathima ◽  
Asutosh Mishra ◽  
Rushali Ghosh ◽  
Shalmali Das

Abstract Modern day scenario has an increasing power demand due to the growing development which indeed increases the load on the generation which might cause turbulence in the system and may bounce out of stability. The governor itself can’t handle such frequent load changes and adjust the generation amount to keep the frequency between the margins. This paper proposes an approach towards such predicament to incorporate an optimization method in order to ensure stability of the system despite the drastic changes in demand. Load frequency control is a control method for maintaining the frequency of the system during the change in demand. Use of controllers has proven to be effective in controlling the frequency deviations in the power systems and the response of the controller is further improved using optimization technique for better stability. The PID controller tuned by Particle Swarm Optimization is employed in multi-area system which reduces the time response by a considerable amount and the deviation settles much quicker despite the rapid load changes. The proposed controller is executed further for renewable energy sources connected to the individual areas and demonstration proves that the optimized controller is efficient enough in handling the frequency deviations when wind and solar with sunlight penetration is incorporated.


Author(s):  
Gerry Liston Putra ◽  
Mitsuru Kitamura ◽  
Akihiro Takezawa

Abstract Most shipyard companies maintain efficiency in all aspects of their business to survive. One of these aspects is ship production costs and their reduction. This study proposes a solution to this problem using an optimization method. A hatch cover composed of plates and stiffeners was selected as a case study. In this study, the mass and material cost of the hatch cover was optimized as an objective function using the Pareto approach with developed optimization methods. Plate thickness t, stiffener shape s, and plate material type m were selected as the design variables in this study along with some constraints. To estimate the optimal plate thickness, an expression of stress equations was Developed using an optimization technique. Furthermore, stiffener shape and plate material type selection were optimized using a genetic algorithm (GA). The results show that the optimization method is effective to decrease the mass and material cost of a hatch cover. Introduction The demand for new shipbuilding has decreased because of the effect of the economic crisis that hit almost every country in the world. Shipyard companies must think innovatively and creatively to survive under the pressure of this crisis by evaluating various studies and improvising new methods to achieve efficiency. One of the studies that has been performed examines the methods to reduce the fabrication cost of ship structures to stay profitable through the optimization of work hours, workflow production systems, and structural design.


Author(s):  
Muhammad Adeel ◽  
Yinglei Song

Background: In many applications of image processing, the enhancement of images is often a step necessary for their preprocessing. In general, for an enhanced image, the visual contrast as a whole and its refined local details are both crucial for achieving accurate results for subsequent classification or analysis. Objective: This paper proposes a new approach for image enhancement such that the global and local visual effects of an enhanced image can both be significantly improved. Methods: The approach utilizes the normalized incomplete Beta transform to map pixel intensities from an original image to its enhanced one. An objective function that consists of two parts is optimized to determine the parameters in the transform. One part of the objective function reflects the global visual effects in the enhanced image and the other one evaluates the enhanced visual effects on the most important local details in the original image. The optimization of the objective function is performed with an optimization technique based on the particle swarm optimization method. Results: Experimental results show that the approach is suitable for the automatic enhancement of images. Conclusion: The proposed approach can significantly improve both the global and visual contrasts of the image.


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