scholarly journals Application of Optimization Method for Calibration and Maintenance of Power-Based Belt Scale

Minerals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 412
Author(s):  
Kanishk Bhadani ◽  
Gauti Asbjörnsson ◽  
Erik Hulthén ◽  
Kristoffer Hofling ◽  
Magnus Evertsson
Keyword(s):  
Mass Flow ◽  
Cost Effective ◽  
Optimization Method ◽  
Conveyor Belt ◽  
Practical Implementation ◽  
Flow Estimation ◽  
Power Draw ◽  
Mass Balancing ◽  
Crushing Plant ◽  
Operational Data

Process optimization and improvement strategies applied in a crushing plant are coupled with the measurement of such improvements, and one of the indicators for improvements is the mass flow at different parts of the circuit. The estimation of the mass flow using conveyor belt power consumption allows for a cost-effective solution. The principle behind the estimation is that the power draw from a conveyor belt is dependent on the load on the conveyor, conveyor speed, geometrical design, and overall efficiency of the conveyor. Calibration of the power-based belt scale is carried out periodically to ensure the accuracy of the measurement. In practical implementation, certain conveyors are not directly accessible for calibration to the physical measurement as these conveyors have limited access or it is too costly to interrupt the ongoing production process. For addressing this limitation, a better strategy is needed to calibrate the efficiency of the power-based belt scale and maintain the reliability of such a system. This paper presents the application of an optimization method for a data collection system to calibrate and maintain accurate mass flow estimation. This includes calibration of variables such as the efficiency of the power-based belt scale. The optimization method uses an error minimization optimization formulation together with the mass balancing of the crushing plant to determine the efficiency of accessible and non-accessible conveyors. Furthermore, a correlation matrix is developed to monitor and detect deviations in the estimation for the mass flow. The methods are applied and discussed for operational data from a full-scale crushing plant.

scholarly journals Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4649
Author(s):  
İsmail Hakkı ÇAVDAR ◽  
Vahit FERYAD
Keyword(s):  
Smart Grids ◽  
Energy Demand ◽  
Optimization Technique ◽  
Cost Effective ◽  
Optimization Method ◽  
Long Term Memory ◽  
Successful Implementation ◽  
Efficient Design ◽  
Energy Disaggregation ◽  
Load Monitoring

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.

scholarly journals Economic Development Based on a Mathematical Model: An Optimal Solution Method for the Fuel Supply of International Road Transport Activity

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2963
Author(s):  
Melinda Timea Fülöp ◽  
Miklós Gubán ◽  
György Kovács ◽  
Mihály Avornicului
Keyword(s):  
Decision Making ◽  
Ad Hoc ◽  
Market Competition ◽  
Optimal Solution ◽  
Cost Savings ◽  
Cost Effective ◽  
Optimization Method ◽  
Optimal Decision ◽  
Environmental Damage ◽  
Fuel Cost

Due to globalization and increased market competition, forwarding companies must focus on the optimization of their international transport activities and on cost reduction. The minimization of the amount and cost of fuel results in increased competition and profitability of the companies as well as the reduction of environmental damage. Nowadays, these aspects are particularly important. This research aims to develop a new optimization method for road freight transport costs in order to reduce the fuel costs and determine optimal fueling stations and to calculate the optimal quantity of fuel to refill. The mathematical method developed in this research has two phases. In the first phase the optimal, most cost-effective fuel station is determined based on the potential fuel stations. The specific fuel prices differ per fuel station, and the stations are located at different distances from the main transport way. The method developed in this study supports drivers’ decision-making regarding whether to refuel at a farther but cheaper fuel station or at a nearer but more expensive fuel station based on the more economical choice. Thereafter, it is necessary to determine the optimal fuel volume, i.e., the exact volume required including a safe amount to cover stochastic incidents (e.g., road closures). This aspect of the optimization method supports drivers’ optimal decision-making regarding optimal fuel stations and how much fuel to obtain in order to reduce the fuel cost. Therefore, the application of this new method instead of the recently applied ad-hoc individual decision-making of the drivers results in significant fuel cost savings. A case study confirmed the efficiency of the proposed method.

scholarly journals Seeking optimal groundwater pumping strategies at Pinggu District in Beijing, China

2012 ◽  
Vol 15 (2) ◽  
pp. 607-619 ◽  
Author(s):  
A. L. Yang ◽  
G. H. Huang ◽  
X. S. Qin ◽  
L. Li ◽  
W. Li
Keyword(s):  
Groundwater Management ◽  
Fuzzy Optimization ◽  
Cost Effective ◽  
Optimization Method ◽  
Chance Constrained Programming ◽  
Groundwater Pumping ◽  
Simulation And Optimization ◽  
Study Results ◽  
Pumping Rates ◽  
Beijing China

A simulation-based fuzzy optimization method (SFOM) was proposed for regional groundwater pumping management in considering uncertainties. SFOM enhanced the traditional groundwater management models by incorporating a response matrix model (RMM) into a fuzzy chance-constrained programming (FCCP) framework. RMM was used to approximate the input–output relationship between pumping actions and subsurface hydrologic responses. Due to its explicit expression, RMM could be easily embedded into an optimization model to help seek cost-effective pumping solutions. A groundwater management case in Pinggu District of Beijing, China, was used to demonstrate the method's applicability. The study results showed that the obtained system cost and pumping rates would vary significantly under different confidence levels of constraints satisfaction. The decision-makers could identify the best groundwater pumping strategy through analyzing the tradeoff between the risk of violating the related water resources conservation target and the economic benefit. Compared with traditional approaches, SFOM was particularly advantageous in linking simulation and optimization models together, and tackling uncertainties using fuzzy chance constraints.

scholarly journals Cost Effective Method for Toxicity Screening of Pharmaceutical Wastewater Containing Inorganic Salts and Harmful Organic Compounds

2019 ◽  
Vol 23 (1) ◽  
pp. 52-63 ◽  
Author(s):  
Elina Strade ◽  
Daina Kalnina
Keyword(s):  
Activated Sludge ◽  
Biological Treatment ◽  
Oxygen Demand ◽  
Cost Effective ◽  
Practical Implementation ◽  
Toxicity Screening ◽  
Pharmaceutical Wastewater ◽  
Cost Effective Method ◽  
Wide Range ◽  
Wastewater Biological Treatment

Abstract Pharmaceutical wastewater biological treatment plants are stressed with multi-component wastewater and unexpected variations in wastewater flow, composition and toxicity. To avoid operational problems and reduced wastewater treatment efficiency, accurate monitoring of influent toxicity on activated sludge microorganisms is essential. This paper outlines how to predict highly toxic streams, which should be avoided, using measurements of biochemical oxygen demand (BOD), if they are made in a wide range of initial concentration. The results indicated that wastewater containing multivalent Al3+ cations showed a strong toxic effect on activated sludge biocenosis irrespectively of dilutions, while toxicity of phenol and formaldehyde containing wastewater decreased considerably with increasing dilution. Activated sludge microorganisms were not sensitive to wastewater containing halogenated sodium salts (NaCl, NaF) and showed high treatment capacity of saline wastewater. Our findings confirm that combined indicators of contamination, such as chemical oxygen demand (COD), alone do not allow evaluating potential toxic influence of wastewater. Obtained results allow identifying key inhibitory substances in pharmaceutical wastewater and evaluating potential impact of new wastewater streams or increased loading on biological treatment system. Proposed method is sensitive and cost effective and has potential for practical implementation in multiproduct pharmaceutical wastewater biological treatment plants.

Analysis and Optimization of a Passive Micromixer With Curved-Shaped Baffles for Efficient Mixing With Low Pressure Loss in Continuous Flow

2010 ◽  
Author(s):  
Cesar A. Cortes-Quiroz ◽  
Alireza Azarbadegan ◽  
Emadaldin Moeendarbary ◽  
Mehrdad Zangeneh
Keyword(s):  
Pressure Loss ◽  
Cost Effective ◽  
Optimization Method ◽  
Secondary Flows ◽  
Design Parameters ◽  
Mixing Efficiency ◽  
Outlet Section ◽  
Optimization Strategy ◽  
Mixing Index ◽  
Trade Offs

Numerical simulations and an optimization method are used to study the design of a planar T-micromixer with curved-shaped baffles in the mixing channel. The mixing efficiency and the pressure loss in the mixing channel have been evaluated for Reynolds number (Re) in the mixing channel in the range 1 to 250. A Mixing index (Mi) has been defined to quantify the mixing efficiency. Three geometric dimensions: radius of baffle, baffles pitch and height of the channel, are taken as design parameters, whereas the mixing index at the outlet section and the pressure loss in the mixing channel are the performance parameters used to optimize the micromixer geometry. To investigate the effect of design and operation parameters on the device performance, a systematic design and optimization methodology is applied, which combines Computational Fluid Dynamics (CFD) with an optimization strategy that integrates Design of Experiments (DOE), Surrogate modeling (SM) and Multi-Objective Genetic Algorithm (MOGA) techniques. The Pareto front of designs with the optimum trade-offs of mixing index and pressure loss is obtained for different values of Re. The micromixer can enhance mixing using the mechanisms of diffusion (lower Re) and convection (higher Re) to achieve values over 90%, in particular for Re in the order of 100 that has been found the cost-effective level for volume flow. This study applies a systematic procedure for evaluation and optimization of a planar T-mixer with baffles in the channel that promote transversal 3-D flow as well as recirculation secondary flows that enhance mixing.

Lignin peroxidase: Optimization of media for higher productivity by single factor optimization method

2021 ◽  
Vol 16 (7) ◽  
pp. 130-135
Author(s):  
Shruti Shukla ◽  
Anjali Padhiar
Keyword(s):  
Lignin Peroxidase ◽  
Cost Effective ◽  
Optimization Method ◽  
Ligninolytic Enzyme ◽  
Mineral Elements ◽  
Inoculum Size ◽  
Chemical Parameters ◽  
Optimization Study ◽  
The Media ◽  
Physical And Chemical

Lignin peroxidase belongs to ligninolytic enzyme group and is one of the industrial important enzymes as it has wide applications in different sectors. Lignin peroxidase is produced by submerged fermentation process which requires optimization of physical and chemical parameters to achieve higher activity and make the process cost effective. The present study aimed at the optimization of physical as well chemical parameters of production medium. The optimization includes physical parameter such as incubation time, inoculum size, temperature, pH, RPM (Rotation per minute) while chemical parameters include carbon source, nitrogen source and different mineral elements. Form the optimization study, it was observed that highest lignin peroxidase production was achieved after 72 hours of incubation at temperature 300C, pH 6 and RPM 120. Optimization of chemical parameters reveals that incorporation of sodium nitrite (9g/L) in the media gave significant increase in enzyme activity. It was found that the maximum productivity achieved after optimization was 2214 U/ml which was four times higher than process without optimized parameters.

Improving Efficiency and Enhancing Productivity in Transporting Fertilizers by Using Conveyor Belt Cleaners

2014 ◽  
Vol 1082 ◽  
pp. 505-510 ◽  
Author(s):  
Tasnim F. Ariff ◽  
Muhd. Fahmi B. Jusoh ◽  
Malek Parnin ◽  
Mohd. Hanif Azenan
Keyword(s):  
Material Handling ◽  
Drainage System ◽  
Cost Effective ◽  
Conveyor Belt ◽  
Material Handling System ◽  
Handling System ◽  
Food Items ◽  
Manual Labour ◽  
The Future ◽  
Conveyor Belts

Conveyor belts are used widely to carry and transport various materials ranging from fertilizers to foods items from the cargo ship to the packaging site. Spillage and carryback problems are common issues relating to transportaion of these types of materials at Malaysian ports. This leads to lots of wastage in fertilizers and food. In addition, extra manual labour work is required to shovel the spillage into the container. This raises the concern of hygiene especially when relating to food items. Furthermore, improper washing and drainage system has also lead to corrosion on the floor. This has resulted in a lot of inefficient work and lack in productivity in the material handling system. Therefore, in order to solve this problem, primary and secondary belt cleaners were designed using CATIA software. These newly improved simple and cost effective designs of the primary and secondary belt cleaners together with a spray shaft and efficient washing box were fabricated, tested and implemented successfully. The spillage was eliminated and with the new washing system, corrosion on the floor can be prevented from occuring in the future.

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