A Hierarchical Method for Large-Scale Two-Dimensional Layout

1983 ◽  
Vol 105 (2) ◽  
pp. 242-248
Author(s):  
K. P. Lam
Keyword(s):  
Large Scale ◽  
Computational Cost ◽  
Optimal Solution ◽  
Good Alternative ◽  
Computational Effort ◽  
Practical Consideration ◽  
Two Dimensional ◽  
Hierarchical Approach ◽  
Variable Window ◽  
Alternative Solutions

The optimal layout problem of allocating different types of rectangular shapes to a large rectangular sheet (also referred to as the two-dimensional knapsack problem) is tackled by a hierarchical approach using the concepts of quad-cut, guillotine-cut, and edge-cut with variable window sizes. The method can handle sheet defects and also allows for the specification of important pieces at a fixed or variable location. In addition, the hierarchical approach has the flexibility of generating different layout patterns with little computational effort once the knapsack function for the largest window has been obtained. Although the method is suboptimal in the sense that it may not achieve the best possible result with minimum waste, extensive simulation indicates that it always gives good alternative solutions at reasonable computational cost; this is in contrast with the optimal solution for large-scale problems which often requires excessive computational effort beyond practical consideration.

A fast method for statistical grammar induction

1998 ◽  
Vol 4 (3) ◽  
pp. 191-209 ◽  
Author(s):  
WIDE R. HOGENHOUT ◽  
YUJI MATSUMOTO
Keyword(s):  
Computational Complexity ◽  
Language Processing ◽  
Large Scale ◽  
Learning Algorithm ◽  
Computational Cost ◽  
Computational Effort ◽  
Fast Method ◽  
Statistical Induction ◽  
Stochastic Context Free Grammars ◽  
Context Free

The statistical induction of stochastic context free grammars from bracketed corpora with the Inside Outside Algorithm is an appealing method for grammar learning, but the computational complexity of this algorithm has made it impossible to generate a large scale grammar. Researchers from natural language processing and speech recognition have suggested various methods to reduce the computational complexity and, at the same time, guide the learning algorithm towards a solution by, for example, placing constraints on the grammar. We suggest a method that strongly reduces that computational cost of the algorithm without placing constraints on the grammar. This method can in principle be combined with any of the constraints on grammars that have been suggested in earlier studies. We show that it is feasible to achieve results equivalent to earlier research, but with much lower computational effort. After creating a small grammar, the grammar is incrementally increased while rules that have become obsolete are removed at the same time. We explain the modifications to the algorithm, give results of experiments and compare these to results reported in other publications.

Development of a Two-Dimensional Thermal Model for Li-Ion Battery Pack With Experimental Validation

2019 ◽  
Vol 12 (2) ◽  
Author(s):  
Haoting Wang ◽  
Ning Liu ◽  
Lin Ma
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Experimental Validation ◽  
Computational Cost ◽  
Battery Pack ◽  
Two Dimensional ◽  
Li Ion Battery ◽  
New Approach ◽  
Battery Packs ◽  
Li Ion

Abstract This paper reports the development of a two-dimensional two states (2D2S) model for the analysis of thermal behaviors of Li-ion battery packs and its experimental validation. This development was motivated by the need to fill a niche in our current modeling capabilities: the need to analyze 2D temperature (T) distributions in large-scale battery packs in real time. Past models were predominately developed to either provide detailed T information with high computational cost or provide real-time analysis but only 1D lumped T information. However, the capability to model 2D T field in real time is desirable in many applications ranging from the optimal design of cooling strategies to onboard monitoring and control. Therefore, this work developed a new approach to provide this desired capability. The key innovations in our new approach involved modeling the whole battery pack as a complete thermal-fluid network and at the same time calculating only two states (surface and core T) for each cell. Modeling the whole pack as a complete network captured the interactions between cells and enabled the accurate resolution of the 2D T distribution. Limiting the calculation to only the surface and core T controlled the computational cost at a manageable level and rendered the model suitable for packs at large scale with many cells.

HEGDE'S INTERFACE NUMERICAL TECHNIQUE FOR RESOLVING QUASI-ONE-DIMENSIONAL NOZZLE FLOWS

2009 ◽  
Vol 06 (01) ◽  
pp. 75-91
Author(s):  
GANESH S. HEGDE ◽  
G. M. MADHU
Keyword(s):  
Truncation Error ◽  
Numerical Solutions ◽  
Numerical Technique ◽  
Computational Cost ◽  
Optimal Solution ◽  
Taylor Series Expansion ◽  
Computational Effort ◽  
Navier Stokes Equation ◽  
One Dimensional ◽  
Interface Theory

Faster convergence, better accuracy and improved stability of the solutions to fluid flow and heat transfer problems in CFD reduce the computational cost and time. The numerical solutions to partial differential equations governing the physical flow and heat phenomena, using computer software and hardware, have been obtained by various techniques which have been refined over the years. The numerical techniques have obtained the base in finite difference method (FDM) approximations derived from Taylor series expansion. Because of linearization, FDM approximations have truncation error creeping into the values of the partial derivatives, which projects an unrealistic picture of the final outcome of results in terms of accuracy, convergence and stability. As the prime objective of this paper, the minimization of truncation error is attempted with the aid of the interface theory (briefly described in the appendix) used as a computational treatment tool. In simple terms, the interface theory provides an optimal solution to all variables in a linear indeterminate system with redundancy in unknowns. The effort has converged in the form of Hegde's interface numerical technique (HINT), which is demonstrated on a quasi-one-dimensional nozzle flow, the physical behavior of which is described by the Navier–Stokes equation considered specific to the said case. HINT could successfully match the results of MacCormack's predictor–corrector method as far as the accuracy is concerned, but with less computational effort and higher productivity. To the knowledge of the authors, HINT may be considered both original and different for its kind in the vast developments in CFD.

Multiharmonic Response Analysis of Systems With Local Nonlinearities Based on Describing Functions and Linear Receptance

2010 ◽  
Vol 132 (3) ◽  
Author(s):  
F. Wei ◽  
G. T. Zheng
Keyword(s):  
Degrees Of Freedom ◽  
Large Scale ◽  
Time Integration ◽  
Computational Cost ◽  
Kinetic Equations ◽  
Computational Effort ◽  
Response Analysis ◽  
Algebraic Equations ◽  
Describing Functions ◽  
And Performance

Direct time integration methods are usually applied to determine the dynamic response of systems with local nonlinearities. Nevertheless, these methods are computationally expensive to predict the steady state response. To significantly reduce the computational effort, a new approach is proposed for the multiharmonic response analysis of dynamical systems with local nonlinearities. The approach is based on the describing function (DF) method and linear receptance data. With the DF method, the kinetic equations are converted into a set of complex algebraic equations. By using the linear receptance data, the dimension of the complex algebraic equations, which should be solved iteratively, are only related to nonlinear degrees of freedom (DOFs). A cantilever beam with a local nonlinear element is presented to show the procedure and performance of the proposed approach. The approach can greatly reduce the size and computational cost of the problem. Thus, it can be applicable to large-scale systems with local nonlinearities.

Computational Approaches for Good Alternative Solutions Based Load Resistance Capacity in Design of Steel Moment-Resisting Frames

2007 ◽  
Vol 347 ◽  
pp. 563-568
Author(s):  
Byoung Han Choi
Keyword(s):  
Optimal Solution ◽  
Load Resistance ◽  
Good Alternative ◽  
Steel Moment Resisting Frames ◽  
Moment Resisting Frames ◽  
Moment Resisting Frame ◽  
Design Alternatives ◽  
Moment Resisting ◽  
Lateral Load Resistance ◽  
Alternative Solutions

A modeling technique to generate good design alternatives from optimal design of steel moment resisting frames is proposed. First presented is the development of Genetic Algorithm(GA)-based approaches that enable designers to identify the best locations for rigid connections in a frame. This GA uses a unique cost function that enables the trade-off study between the number of rigid connections and total cost. Second, the optimization formulation is modified to generate alternatives with a cost comparable to that of the optimal solution. It enables engineers to compare different solutions on the basis of the structure’s lateral load resistance capacity along with incidental factors like the location of the rigid connections, number of different section types, column splices etc. An example of a 5-story and 5-bay steel moment resisting frame is provided to illustrate the effectiveness of the proposed study.

Multi-Objective Reliability-Based Optimization with Stochastic Metamodels

2011 ◽  
Vol 19 (4) ◽  
pp. 525-560 ◽  
Author(s):  
Rajan Filomeno Coelho ◽  
Philippe Bouillard
Keyword(s):  
Structural Engineering ◽  
Large Scale ◽  
Optimization Problems ◽  
Probability Distributions ◽  
Computational Cost ◽  
Continuous Optimization ◽  
Computational Effort ◽  
Kriging Interpolation ◽  
Simulation Code ◽  
Continuous Optimization Problems

This paper addresses continuous optimization problems with multiple objectives and parameter uncertainty defined by probability distributions. First, a reliability-based formulation is proposed, defining the nondeterministic Pareto set as the minimal solutions such that user-defined probabilities of nondominance and constraint satisfaction are guaranteed. The formulation can be incorporated with minor modifications in a multiobjective evolutionary algorithm (here: the nondominated sorting genetic algorithm-II). Then, in the perspective of applying the method to large-scale structural engineering problems—for which the computational effort devoted to the optimization algorithm itself is negligible in comparison with the simulation—the second part of the study is concerned with the need to reduce the number of function evaluations while avoiding modification of the simulation code. Therefore, nonintrusive stochastic metamodels are developed in two steps. First, for a given sampling of the deterministic variables, a preliminary decomposition of the random responses (objectives and constraints) is performed through polynomial chaos expansion (PCE), allowing a representation of the responses by a limited set of coefficients. Then, a metamodel is carried out by kriging interpolation of the PCE coefficients with respect to the deterministic variables. The method has been tested successfully on seven analytical test cases and on the 10-bar truss benchmark, demonstrating the potential of the proposed approach to provide reliability-based Pareto solutions at a reasonable computational cost.

On the Optimal Precoder Design for Energy-Efficient and Secure MIMO Systems

2017 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Tung T. Vu ◽  
Ha Hoang Kha
Keyword(s):  
Energy Efficiency ◽  
Mimo Systems ◽  
Search Algorithm ◽  
Multiple Input Multiple Output ◽  
Research Work ◽  
Computational Cost ◽  
Optimal Solution ◽  
Secrecy Rate ◽  
Highly Nonlinear ◽  
Precoder Design

In this research work, we investigate precoder designs to maximize the energy efficiency (EE) of secure multiple-input multiple-output (MIMO) systems in the presence of an eavesdropper. In general, the secure energy efficiency maximization (SEEM) problem is highly nonlinear and nonconvex and hard to be solved directly. To overcome this difficulty, we employ a branch-and-reduce-and-bound (BRB) approach to obtain the globally optimal solution. Since it is observed that the BRB algorithm suffers from highly computational cost, its globally optimal solution is importantly served as a benchmark for the performance evaluation of the suboptimal algorithms. Additionally, we also develop a low-complexity approach using the well-known zero-forcing (ZF) technique to cancel the wiretapped signal, making the design problem more amenable. Using the ZF based method, we transform the SEEM problem to a concave-convex fractional one which can be solved by applying the combination of the Dinkelbach and bisection search algorithm. Simulation results show that the ZF-based method can converge fast and obtain a sub-optimal EE performance which is closed to the optimal EE performance of the BRB method. The ZF based scheme also shows its advantages in terms of the energy efficiency in comparison with the conventional secrecy rate maximization precoder design.

Solution‐Processed Large‐Scale Concentric‐Ring Laser on Two‐Dimensional Ruddlesden–Popper Perovskites Thin Films

2021 ◽  
pp. 2100193
Author(s):  
Peng Liu ◽  
Bingqian Zhang ◽  
Qing Liao ◽  
Guifen Tian ◽  
Chunling Gu ◽  
...  
Keyword(s):  
Thin Films ◽  
Ring Laser ◽  
Large Scale ◽  
Two Dimensional ◽  
Concentric Ring ◽  
Solution Processed

Large-scale visualization of dispersion of liquid-exfoliated two-dimensional nanosheets

2021 ◽  
Author(s):  
Xingyu Cui ◽  
Wen ying Shi ◽  
Chao Lu
Keyword(s):  
Aqueous Solution ◽  
Large Scale ◽  
Fluorescence Microscope ◽  
Visualization Method ◽  
Two Dimensional ◽  
Non Invasive

An ultrafast, non-invasive and large-scale visualization method has been developed to evaluate the dispersion of two-dimensional nanosheets in aqueous solution with fluorescence microscope by formation of excimers from improvement of...

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