scholarly journals Performance And Reliability Improvement In Intercalated MLGNR Interconnects Using Optimized Aspect Ratio

2021 ◽  
Author(s):  
Bhawana Kumari ◽  
Rohit Sharma ◽  
Manodipan Sahoo
Keyword(s):  
Aspect Ratio ◽  
Power Efficiency ◽  
Performance Metrics ◽  
Cost Effective ◽  
Optimization Method ◽  
Numerical Approach ◽  
Technology Scaling ◽  
Scaling Down ◽  
Improved Performance ◽  
Power Delay Product

Abstract In this work, aspect ratio of various intercalation doped MLGNR interconnects are optimized using a numerical approach toachieve improved performance and reliability. A numerical optimization method is presented to estimate optimized aspect ratio considering combined effects of performance, noise and reliability metrics for any arbitrary nano interconnect system. This approach is cost effective and will be extremely useful to industry for selection of aspect ratio of interconnects as it is a non-SPICE method and reduces fabrication iterations for achieving desired performance and reliability. Our numerical method suggests that by minimizing the figure of merit (i.e. Noise Delay Power Product (NPDP) / Breakdown Power PBD ratio), aspect ratio of FeCl3 doped MLGNR interconnect is optimized at 0.987, 0.61 and 0.579 for local, intermediate and global level, respectively at 7 nm node. Comparing the optimized performance metrics in this work with the estimated metrics at prescribed aspect ratio by IRDS roadmap, delay, noise delay product (NDP), power delay product (PDP), PDP/PBD ratio and figure of meritare improved by (∼2% and ∼25%), (∼44% and ∼50%), (∼9% and ∼48%), (∼6% and ∼48%) and (∼49% and ∼68%) for 10 µm and 1 mm long FeCl3 doped MLGNR interconnect, respectively at 7 nm node. Increase in contact resistance leads to significant decrease in performance and increase in optimized aspect ratio of local FeCl3 doped MLGNR interconnect. Scaling down from 10 nm to 7 nm node results in increase of optimized aspect ratio in all levels of interconnects. Even though theperformance of MLGNR degrades with scaling down but when compared to copper, the performance improves with technology scaling. Finally, this study provides circuit designers a detailed guideline for selecting an optimized aspect ratio for achieving better performance, power efficiency and reliability in doped MLGNR interconnects.

Optimization of a Centrifugal Pump Impeller: Coupling a Hybrid Stochastic Method to a Potential Flow Solver

2009 ◽  
Author(s):  
Nikolas Antonakis
Keyword(s):  
Potential Flow ◽  
Design Space ◽  
Hybrid Approach ◽  
Cost Effective ◽  
Optimization Methods ◽  
Optimization Method ◽  
Population Based ◽  
Pump Impeller ◽  
Flow Solver ◽  
Improved Performance

An optimization process is employed to improve the performance of an industrial radial flow pump impeller. A hybrid optimization scheme is coupled to a cost effective potential flow solver that computes the flow through the blade channel. The impeller geometry is parameterized to reproduce variations over a wide design space and the objective function is evaluated at each iteration to account for the performance of each candidate blade. The concept of the hybrid approach is to employ a global stochastic optimization method for the diversification of the design space and a deterministic local method for efficiently intensifying the search towards the optimum. The trend of computer industry to multi-core processors is a promising platform for population based optimization methods and even on a quad core the timescales needed to solve the problem with the proposed methodology are reasonable. Results present an optimised impeller with improved performance but also a clear trade-off among contradictory design objectives.

Application of Fast Laser Deprocessing Techniques in Physical Failure Analysis on SRAM Memory of Advance Technology

2014 ◽  
Author(s):  
H.H. Yap ◽  
P.K. Tan ◽  
G.R. Low ◽  
M.K. Dawood ◽  
H. Feng ◽  
...  
Keyword(s):  
Failure Analysis ◽  
Integrated Circuit ◽  
Cost Effective ◽  
Tetraethyl Orthosilicate ◽  
Ic Design ◽  
Advance Technology ◽  
Defect Identification ◽  
Technology Scaling ◽  
And Function ◽  
Metal Layers

Abstract With technology scaling of semiconductor devices and further growth of the integrated circuit (IC) design and function complexity, it is necessary to increase the number of transistors in IC’s chip, layer stacks, and process steps. The last few metal layers of Back End Of Line (BEOL) are usually very thick metal lines (>4μm thickness) and protected with hard Silicon Dioxide (SiO2) material that is formed from (TetraEthyl OrthoSilicate) TEOS as Inter-Metal Dielectric (IMD). In order to perform physical failure analysis (PFA) on the logic or memory, the top thick metal layers must be removed. It is time-consuming to deprocess those thick metal and IMD layers using conventional PFA workflows. In this paper, the Fast Laser Deprocessing Technique (FLDT) is proposed to remove the BEOL thick and stubborn metal layers for memory PFA. The proposed FLDT is a cost-effective and quick way to deprocess a sample for defect identification in PFA.

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 A Two-Stage Mono- and Multi-Objective Method for the Optimization of General UPS Parallel Manipulators

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 543
Author(s):  
Alejandra Ríos ◽  
Eusebio E. Hernández ◽  
S. Ivvan Valdez
Keyword(s):  
Genetic Algorithm ◽  
Performance Metrics ◽  
Tracking Error ◽  
Parallel Manipulators ◽  
Optimization Method ◽  
Statistical Hypothesis ◽  
Two Stage ◽  
Multi Objective ◽  
Second Stage ◽  
Conflicting Objectives

This paper introduces a two-stage method based on bio-inspired algorithms for the design optimization of a class of general Stewart platforms. The first stage performs a mono-objective optimization in order to reach, with sufficient dexterity, a regular target workspace while minimizing the elements’ lengths. For this optimization problem, we compare three bio-inspired algorithms: the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO), and the Boltzman Univariate Marginal Distribution Algorithm (BUMDA). The second stage looks for the most suitable gains of a Proportional Integral Derivative (PID) control via the minimization of two conflicting objectives: one based on energy consumption and the tracking error of a target trajectory. To this effect, we compare two multi-objective algorithms: the Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D) and Non-dominated Sorting Genetic Algorithm-III (NSGA-III). The main contributions lie in the optimization model, the proposal of a two-stage optimization method, and the findings of the performance of different bio-inspired algorithms for each stage. Furthermore, we show optimized designs delivered by the proposed method and provide directions for the best-performing algorithms through performance metrics and statistical hypothesis tests.

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.

A new jig-shape optimization method for the high aspect ratio wing

2018 ◽  
Vol 91 (1) ◽  
pp. 124-133
Author(s):  
Zhe Yuan ◽  
Shihui Huo ◽  
Jianting Ren
Keyword(s):  
Aspect Ratio ◽  
Shape Optimization ◽  
High Aspect Ratio ◽  
Optimization Design ◽  
Design Method ◽  
Aircraft Design ◽  
Optimization Method ◽  
Attack Angle ◽  
Structural Deformation ◽  
Content Type

Purpose Computational efficiency is always the major concern in aircraft design. The purpose of this research is to investigate an efficient jig-shape optimization design method. A new jig-shape optimization method is presented in the current study and its application on the high aspect ratio wing is discussed. Design/methodology/approach First, the effects of bending and torsion on aerodynamic distribution were discussed. The effect of bending deformation was equivalent to the change of attack angle through a new equivalent method. The equivalent attack angle showed a linear dependence on the quadratic function of bending. Then, a new jig-shape optimization method taking integrated structural deformation into account was proposed. The method was realized by four substeps: object decomposition, optimization design, inversion and evaluation. Findings After the new jig-shape optimization design, both aerodynamic distribution and structural configuration have satisfactory results. Meanwhile, the method takes both bending and torsion deformation into account. Practical implications The new jig-shape optimization method can be well used for the high aspect ratio wing. Originality/value The new method is an innovation based on the traditional single parameter design method. It is suitable for engineering application.

A New Concept of a Two-Dimensional Supersonic Relative Inlet Mach Number Compressor Cascade

2009 ◽  
Author(s):  
Toyotaka Sonoda ◽  
Markus Olhofer ◽  
Toshiyuki Arima ◽  
Bernhard Sendhoff
Keyword(s):  
Mach Number ◽  
Total Pressure ◽  
Optimization Method ◽  
Superior Performance ◽  
Compressor Cascade ◽  
Pressure Loss Coefficient ◽  
Supersonic Inlet ◽  
Flow Mechanisms ◽  
Improved Performance ◽  
Total Pressure Loss Coefficient

In this study, a numerical shape optimization method based on evolutionary algorithms coupled with a verified CFD solver has been applied to the ambitious target of a shock free 2-D supersonic inlet Mach number compressor cascade. The study is based on the DLR-PAV-1.5 supersonic compressor cascade designed by the pre-compression blading concept. The DLR cascade airfoil has been optimized using a verified CFD code. A superior performance of the optimized supersonic cascade with about 24% reduction of the total pressure loss coefficient compared to the original cascade has been realized. The flow mechanisms observable around the blade with improved performance and the resulting design concept are discussed in this paper.

scholarly journals Investigating the practical viability of walk-sharing in improving pedestrian safety

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Debjit Bhowmick ◽  
Stephan Winter ◽  
Mark Stevenson ◽  
Peter Vortisch
Keyword(s):  
Public Perception ◽  
Performance Metrics ◽  
Social Preferences ◽  
Cost Effective ◽  
Pedestrian Safety ◽  
Web Based ◽  
Proactive Approach ◽  
Community Acceptance ◽  
Urban Scenario ◽  
Spatio Temporal

AbstractWalk-sharing is a cost-effective and proactive approach that promises to improve pedestrian safety and has been shown to be technically (theoretically) viable. Yet, the practical viability of walk-sharing is largely dependent on community acceptance, which has not, until now, been explored. Gaining useful insights on the community’s spatio-temporal and social preferences in regard to walk-sharing will ensure the establishment of practical viability of walk-sharing in a real-world urban scenario. We aim to derive practical viability using defined performance metrics (waiting time, detour distance, walk-alone distance and matching rate) and by investigating the effectiveness of walk-sharing in terms of its major objective of improving pedestrian safety and safety perception. We make use of the results from a web-based survey on the public perception on our proposed walk-sharing scheme. Findings are fed into an existing agent-based walk-sharing model to investigate the performance of walk-sharing and deduce its practical viability in urban scenarios.

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