scholarly journals Perspective Solutions for the Design of Drilling Tools

2019 ◽  
Vol 105 ◽  
pp. 03027 ◽  
Author(s):  
Ulugbek Mannanov ◽  
Javokhir Toshov ◽  
Lazizjon Toshniyozov
Keyword(s):  
Energy Consumption ◽  
Dynamic Systems ◽  
Optimization Problems ◽  
Bottom Hole ◽  
Drill Bits ◽  
Drilling Tools

The article considers the ways to solve optimization problems of drill bits on a deterministic basis through studying and using the “Regularity of energy consumption of dynamic systems from resistance to motion forces”, which directly indicates the causes of bit balling formation, the reasons for the insufficient stability of the bearing assemblies of the cones, the causes of instability of the drill bits at the bottom of the well. Theoretical grounded search was done to use certain methods for designing drill bits of cutting-abrasive type, working in the rotational steam mode, which determine uniform wear of armaments for all crowns of working matrices and uniform destruction of the rock through all of the annular bottom hole.

scholarly journals Optimization of injection molding process for car fender in consideration of energy efficiency and product quality

2014 ◽  
Vol 1 (4) ◽  
pp. 256-265 ◽  
Author(s):  
Hong Seok Park ◽  
Trung Thanh Nguyen
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Injection Molding ◽  
Product Quality ◽  
Process Parameters ◽  
Optimization Problems ◽  
Computational Cost ◽  
Injection Molding Process ◽  
Molding Process ◽  
Nsga Ii

Abstract Energy efficiency is an essential consideration in sustainable manufacturing. This study presents the car fender-based injection molding process optimization that aims to resolve the trade-off between energy consumption and product quality at the same time in which process parameters are optimized variables. The process is specially optimized by applying response surface methodology and using nondominated sorting genetic algorithm II (NSGA II) in order to resolve multi-object optimization problems. To reduce computational cost and time in the problem-solving procedure, the combination of CAE-integration tools is employed. Based on the Pareto diagram, an appropriate solution is derived out to obtain optimal parameters. The optimization results show that the proposed approach can help effectively engineers in identifying optimal process parameters and achieving competitive advantages of energy consumption and product quality. In addition, the engineering analysis that can be employed to conduct holistic optimization of the injection molding process in order to increase energy efficiency and product quality was also mentioned in this paper.

Location and Provisioning Problems in Cloud Computing Networks

2013 ◽  
pp. 22-45 ◽  
Author(s):  
Federico Larumbe ◽  
Brunilde Sansò
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Data Centers ◽  
Optimization Problems ◽  
Virtual Machine Placement ◽  
Future Research ◽  
Network Efficiency ◽  
Placement Problem ◽  
The Cost

This chapter addresses a set of optimization problems that arise in cloud computing regarding the location and resource allocation of the cloud computing entities: the data centers, servers, software components, and virtual machines. The first problem is the location of new data centers and the selection of current ones since those decisions have a major impact on the network efficiency, energy consumption, Capital Expenditures (CAPEX), Operational Expenditures (OPEX), and pollution. The chapter also addresses the Virtual Machine Placement Problem: which server should host which virtual machine. The number of servers used, the cost, and energy consumption depend strongly on those decisions. Network traffic between VMs and users, and between VMs themselves, is also an important factor in the Virtual Machine Placement Problem. The third problem presented in this chapter is the dynamic provisioning of VMs to clusters, or auto scaling, to minimize the cost and energy consumption while satisfying the Service Level Agreements (SLAs). This important feature of cloud computing requires predictive models that precisely anticipate workload dimensions. For each problem, the authors describe and analyze models that have been proposed in the literature and in the industry, explain advantages and disadvantages, and present challenging future research directions.

scholarly journals A Dual-Objective Substation Energy Consumption Optimization Problem in Subway Systems

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1876 ◽  
Author(s):  
Hongjie Liu ◽  
Tao Tang ◽  
Jidong Lv ◽  
Ming Chai
Keyword(s):  
Energy Consumption ◽  
Energy Storage ◽  
Energy Conservation ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Energy Utilization ◽  
Total Size ◽  
Energy Consumption Optimization ◽  
Regenerative Energy ◽  
Timetable Optimization

Maximizing regenerative energy utilization is an important way to reduce substation energy consumption in subway systems. Timetable optimization and energy storage systems are two main ways to improve improve regenerative energy utilization, but they were studied separately in the past. To further improve energy conservation while maintaining a low cost, this paper presents a strategy to improve regenerative energy utilization by an integration of them, which determines the capacity of each Wayside Energy Storage System (WESS) and correspondingly optimizes the timetable at the same time. We first propose a dual-objective optimization problem to simultaneously minimize substation energy consumption and the total cost of WESS. Then, a mathematical model is formulated with the decision variables as the configuration of WESS and timetable. Afterwards, we design an ϵ -constraint method to transform the dual-objective optimization problem into several single-objective optimization problems, and accordingly design an improved artificial bee colony algorithm to solve them sequentially. Finally, numerical examples based on the actual data from a subway system in China are conducted to show the effectiveness of the proposed method. Experimental results indicate that substation energy consumption is effectively reduced by using WESS together with a correspondingly optimized timetable. Note that substation energy consumption becomes lower when the total size of WESS is larger, and timetable optimization further reduces it. A set of Pareto optimal solutions is obtained for the experimental subway line—based on which, decision makers can make a sensible trade-off between energy conservation and WESS investment accordingly to their preferences.

scholarly journals Privacy-Aware Online Task Offloading for Mobile-Edge Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Dali Zhu ◽  
Ting Li ◽  
Haitao Liu ◽  
Jiyan Sun ◽  
Liru Geng ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Mobile Devices ◽  
Mobile Networks ◽  
Location Privacy ◽  
Optimization Problems ◽  
Energy Performance ◽  
Edge Computing ◽  
System Level ◽  
Mobile Edge Computing ◽  
Task Offloading

Mobile edge computing (MEC) has been envisaged as one of the most promising technologies in the fifth generation (5G) mobile networks. It allows mobile devices to offload their computation-demanding and latency-critical tasks to the resource-rich MEC servers. Accordingly, MEC can significantly improve the latency performance and reduce energy consumption for mobile devices. Nonetheless, privacy leakage may occur during the task offloading process. Most existing works ignored these issues or just investigated the system-level solution for MEC. Privacy-aware and user-level task offloading optimization problems receive much less attention. In order to tackle these challenges, a privacy-preserving and device-managed task offloading scheme is proposed in this paper for MEC. This scheme can achieve near-optimal latency and energy performance while protecting the location privacy and usage pattern privacy of users. Firstly, we formulate the joint optimization problem of task offloading and privacy preservation as a semiparametric contextual multi-armed bandit (MAB) problem, which has a relaxed reward model. Then, we propose a privacy-aware online task offloading (PAOTO) algorithm based on the transformed Thompson sampling (TS) architecture, through which we can (1) receive the best possible delay and energy consumption performance, (2) achieve the goal of preserving privacy, and (3) obtain an online device-managed task offloading policy without requiring any system-level information. Simulation results demonstrate that the proposed scheme outperforms the existing methods in terms of minimizing the system cost and preserving the privacy of users.

scholarly journals Stressed State of Elements of Dismountable Drilling Tool with Spherical Cutters: Simulation in Software Environment

2019 ◽  
Vol 9 (2) ◽  
pp. 3499-3504
Keyword(s):  
Stressed State ◽  
Equivalent Stress ◽  
Mining Industry ◽  
Complete Information ◽  
Drill Bit ◽  
Software Environment ◽  
Drilling Tool ◽  
Heterogeneous Distribution ◽  
Drill Bits ◽  
Drilling Tools

Advance in extraction of mineral resources is one of the most prioritized problems of mining industry in Russia and other countries. Herewith, drilling and blasting operations are the most important mining stages, the relevant expenses reach up to 50% of total mining costs. Drilling tool is the most important and highly loaded element of drilling assembly determining the efficiency of blasthole drilling. Existing designs of drill bits of Russian and foreign manufacturers are nondismountable, that is, are beyond repair or reclaim, especially in field conditions. For instance, in the case of failure of one bearing support, the drill bit fails and is rejected. Despite numerous types of drilling tools, their stressed state has been studied sufficiently only for serially fabricated drill bits. Therefore, it is important to study strength properties of dismountable drilling tools which provide the maximum operation lifetime of the basic parts (body and coupling). Complete information about loads acting on the main elements of drill bits is required to improve designs of dismountable drilling tools. This work analyzes stress and strain state of dismountable drill bits with spherical cutters (RSShD) using finite element models in ANSYS software environment. Predictions are made for the cases of maximum loads exerted by highly efficient drilling rigs on the drill bit and heterogeneous distribution of these loads over elements of the drill bit. Distributions of equivalent stress fields occurring in drill bit body, bearing supports and cutters are presented. Drill bit operability in various operation modes is analyzed

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