scholarly journals Robust Optimization of Road Vehicle Suspension Considering the Variation of Tire Vertical Stiffness

2019 ◽  
Vol 11 (1) ◽  
pp. 8-15
Author(s):  
Liunan Yang ◽  
Federico Ballo ◽  
Giorgio Previati ◽  
Massimiliano Gobbi
Keyword(s):  
Robust Optimization ◽  
Optimization Technique ◽  
Optimization Method ◽  
Suspension Spring ◽  
Vertical Stiffness ◽  
Working Space ◽  
Road Profile ◽  
Expected Performance ◽  
Stiffness And Damping Coefficient ◽  
The One

Tire vertical stiffness is influenced by many factors. The inflation pressure, tire dimension, and usage of run-flat tire are considered in this paper. Robust multi-objective optimization technique is used to optimize the suspension performance considering the variation of the tire vertical stiffness. Three objective functions, discomfort, road holding, and working space are used to evaluate the dynamic behavior of the suspension considering a two-degree-of-freedom quarter-car model excited by a random road profile. The Pareto-optimal solutions in terms of suspension spring stiffness and damping coefficient are obtained and compared with the one computed by means of a deterministic approach. Solutions obtained by means of the robust optimization method are proven to be less sensitive to the possible variations of the tire vertical stiffness without influencing significantly the expected performance.

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.

Well Placement Technique and Production Optimization for Mature Field - A Case Study of L-X Field

2020 ◽  
Vol 46 ◽  
pp. 168-179
Author(s):  
Patrick Nwafor ◽  
Kelani Bello
Keyword(s):  
Oil And Gas ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Oil And Gas Industry ◽  
Optimization Method ◽  
Simulation Software ◽  
Production Optimization ◽  
Direct Optimization ◽  
Well Placement ◽  
Local Optimal Solution

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.

Mean Temperature Difference Charts for Air Coolers

1983 ◽  
Vol 105 (3) ◽  
pp. 592-597 ◽  
Author(s):  
A. Pignotti ◽  
G. O. Cordero
Keyword(s):  
Heat Transfer ◽  
Heat Capacity ◽  
Temperature Difference ◽  
Optimization Technique ◽  
Independent Variables ◽  
Mean Temperature ◽  
Air Cooler ◽  
The Mean ◽  
The One ◽  
Water Ratio

Computer generated graphs are presented for the mean temperature difference in typical air cooler configurations, covering the combinations of numbers of passes and rows per pass of industrial interest. Two sets of independent variables are included in the graphs: the conventional one (heat capacity water ratio and cold fluid effectiveness), and the one required in an optimization technique of widespread use (hot fluid effectiveness and the number of heat transfer units). Flow arrangements with side-by-side and over-and-under passes, frequently found in actual practice, are discussed through examples.

An Enhanced One-Layer Passive Microfluidic Mixer With an Optimized Lateral Structure With the Dean Effect

2015 ◽  
Vol 137 (9) ◽  
Author(s):  
Teng Zhou ◽  
Yifan Xu ◽  
Zhenyu Liu ◽  
Sang Woo Joo
Keyword(s):  
Reynolds Number ◽  
Topology Optimization ◽  
Optimization Method ◽  
Mixing Efficiency ◽  
Boolean Operation ◽  
Microfluidic Mixer ◽  
Wide Range ◽  
The One ◽  
Lateral Structure ◽  
Topology Optimization Method

Topology optimization method is applied to a contraction–expansion structure, based on which a simplified lateral flow structure is generated using the Boolean operation. A new one-layer mixer is then designed by sequentially connecting this lateral structure and bent channels. The mixing efficiency is further optimized via iterations on key geometric parameters associated with the one-layer mixer designed. Numerical results indicate that the optimized mixer has better mixing efficiency than the conventional contraction–expansion mixer for a wide range of the Reynolds number.

Design rules for timber log reciprocal floors, based on mass optimization under stiffness constraint

2021 ◽  
pp. 095605992110416
Author(s):  
Pierre Latteur ◽  
Julien Geno ◽  
Marie Vandamme
Keyword(s):  
Parametric Design ◽  
Optimization Method ◽  
Equilibrium Equations ◽  
Design Rules ◽  
Stiffness Optimization ◽  
Structural Relevance ◽  
Reciprocal Structures ◽  
General Mass ◽  
The One ◽  
Robotic Tools

Building with raw timber allows to reduce the price of construction and to make it more competitive with respect to concrete or steel construction. For a few years now, the combination of parametric design and robotic tools make possible the fast and precise milling of timber logs for their accurate connection. However, the spans are quickly limited by the logs length. In this context, reciprocal structures are relevant, since they allow to build large spans structures with short beams. Finally, the architectural interest of reciprocal structures is not to prove. However, the choice of the most efficient reciprocal frame, as well as its structural relevance in terms of mass and stiffness is, most of the time, ruled by subjective considerations. This paper focuses on rectangular floors composed of reciprocal moduli and has three objectives: (1) to develop a general mass and stiffness optimization method for reciprocal floors, which is not only necessary to limit the price, but also to reduce their thickness, (2) to define design rules for reciprocal floors, in particular for the choice of the best engagement ratio, and (3) to compare the structural efficiency of reciprocal floors with the one of “traditional” floors with parallel logs. Coming from a dimensionless transformation of the equilibrium equations, the results of this article will thus give the designers keys to better design reciprocal structures, evaluate their structural performances and relevance, and justify their choices.

Optimization Design of an Axial-Flow Fan Used in Local Ventilation in Mining Industry

2011 ◽  
Author(s):  
Dhaval Desai ◽  
Jiang Zhou
Keyword(s):  
Optimization Design ◽  
Optimization Technique ◽  
Mining Industry ◽  
Axial Flow ◽  
Optimization Method ◽  
Low Noise ◽  
Design Constraint ◽  
Engineering Research ◽  
Blade Element Theory ◽  
Local Ventilation

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.

scholarly journals An enhanced krill herd optimization technique used for classification problem

2021 ◽  
Vol 30 (2) ◽  
pp. 354-364
Author(s):  
Firas Al-Mashhadani ◽  
Ibrahim Al-Jadir ◽  
Qusay Alsaffar
Keyword(s):  
Machine Learning ◽  
Simulated Annealing ◽  
Optimization Technique ◽  
Optimization Method ◽  
Classification Problem ◽  
Test Results ◽  
Internal Evaluation ◽  
Evaluation Measures ◽  
Search Optimization ◽  
Krill Herd

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.

scholarly journals Gaussian Process Regression Based Robust Optimization with Observer Uncertainty for Reconfigurable Self-x Sensory Electronics for Industry 4.0

2021 ◽  
Vol 88 (s1) ◽  
pp. s83-s88
Author(s):  
Qummar Zaman ◽  
Senan Alraho ◽  
Andreas König
Keyword(s):  
Robust Optimization ◽  
Gaussian Process ◽  
Industry 4.0 ◽  
Performance Metrics ◽  
Optimization Technique ◽  
Gaussian Process Regression ◽  
Search Space ◽  
Instrumentation Amplifier ◽  
Statistical Regression ◽  
Current Feedback

Abstract This paper presents a robust optimization technique for the reconfigurable measurement of sensory electronics for industry 4.0 to obtain a robust solution even in the presence of observer uncertainty using a cost-effective performance measurement method. The extrinsic evaluation of the proposed methodology is performed on an indirect current-feedback instrumentation amplifier (CFIA), which is a fundamental part of sensory systems. To reduce the CFIA device performance evaluation set-up cost, a low-cost test stimulus is applied to the circuit under test, and the output response of the circuit is examined to correlate with the device’s performance parameters. Due to the complexity of the smart sensory electronics search space, the meta-heuristic optimization algorithm is being selected as an optimizer. For objective space or observer uncertainty, the Gaussian process regression from the Bayesian statistical regression process is used to estimate the uncertainty level efficiently. Six different classical metrics have been used to evaluate the regression model accuracy. The highest achieved average expected error metrics value is 0.313, and the minimum value of correlation performance metrics is 0.908. The device is implemented using 0.35 μm austriamicrosystems technology.

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