Optimal Operation of Reservoir Systems using Simulated Annealing

A stochastic search technique, simulated annealing (SA), is used to optimize the operation of multiple reservoirs. Seminal application of annealing technique in general to multi-period, multiple-reservoir systems, along with problem representation and selection of different parameter values used in the annealing algorithm for specific cases is discussed. The search technique is improved with the help of heuristic rules, problem-specific information and concepts from the field of evolutionary algorithms. The technique is tested for application to a benchmark problem of four-reservoir system previously solved using a linear programming formulation and its ability to replicate the global optimum solution is examined. The technique is also applied to a system of four hydropower generating reservoirs in Manitoba, Canada, to derive optimal operating rules. A limited version of this problem is solved using a mixed integer nonlinear programming and results are compared with those obtained using SA. A better objective function value is obtained using simulated annealing than the value from a mixed integer non-linear programming model developed for the same problem. Results obtained from these applications suggest that simulated annealing can be used for obtaining near-optimal solutions for multi-period reservoir operation problems that are computationally intractable.     

Comparison of Representative Heuristic Algorithms for Multi-Objective Reservoir Optimal Operation

Heuristic algorithms (HAs) are widely used in multi-objective reservoir optimal operation (MOROO) due to the rapidity of the calculation and simplicity of their design. The literature usually focuses on one or two categories of HAs and simply reviews the state of the art. To provide an overall understanding and a specific comparison of HAs in MOROO, differential evolution (DE), particle swarm optimisation (PSO), and artificial physics optimisation (APO), which serve as typical examples of the three categories of HAs, are compared in terms of the development and applications using a designed experiment. Besides, the general model with constraints and fitness function, and the solution process using a hybrid feasible domain restoration method and penalty function method are also presented. Taking a designed experiment with multiple scenarios, the mean average of the optimal objective function values, the standard deviation of optimal objective function values, the mean average of the computational time, and population diversity are used for comparisons. Results of the comparisons show that (a) the problem of optimal multipurpose reservoir long-term operation is a mathematic programming problem with narrow feasible region and monotonic objective function; (b) it is easy to obtain the same optimal objective function value, but different optimal solutions using HAs; and (c) comparisons do not result in a clear winner, but DE can be more appropriate for MOROO.

     

Parsing human skeletons in an operating room

Multiple human pose estimation is an important yet challenging problem. In an operating room (OR) environment, the 3D body poses of surgeons and medical staff can provide important clues for surgical workflow analysis. For that purpose, we propose an algorithm for localizing and recovering body poses of multiple human in an OR environment under a multi-camera setup. Our model builds on 3D Pictorial Structures and 2D body part localization across all camera views, using convolutional neural networks (ConvNets). To evaluate our algorithm, we introduce a dataset captured in a real OR environment. Our dataset is unique, challenging and publicly available with annotated ground truths. Our proposed algorithm yields to promising pose estimation results on this dataset.     

One View of the Future

Abstract

Floods, droughts, water scarcity, and water contamination are some among many water problems that are present today and will be even more noticeable in the future. In the past, many different tools have been used for simulation and optimization of complex water resources systems in order to provide an improved basis for decision making. The continuing evolution of information technology (hardware and software) creates a good environment for the transition to new tools. Application of the systems approach to water resources planning, management, and operations has been established as one of the most important advances made in the field of water resources engineering. Based on the lessons learned, this contribution provides my personal view on the tools to be used in the future. Two paradigm shifts are discussed. The first one is focusing on the complexity of the water resources domain and the complexity of the modelling tools in an environment characterised by continuous rapid technological development. The second one deals with water-related data availability and natural variability of domain variables in time and space affecting the uncertainty of water resources decision making.     

Decentralized fault detection and diagnosis via sparse PCA based decomposition and Maximum Entropy decision fusion

This paper proposes an approach for decentralized fault detection and diagnosis in process monitoring sensor networks. The sensor network is decomposed into multiple, potentially overlapping, blocks using the Sparse Principal Component Analysis algorithm. Local predictions are generated at each block using Support Vector Machine classifiers. The local predictions are then fused via a Maximum Entropy algorithm. Empirical studies on the benchmark Tennessee Eastman Process data demonstrated that the proposed decentralized approach achieves accuracy comparable to that of the fully centralized approach, while offering benefits in terms of fault tolerance, reusability, and scalability.     

A Mathematical Model for the Calculation of the Adhesion of a Flame Sprayed Coating of Aluminum on S 235 JR Steel

In this work the method of response surfaces was used for the purpose of drawing up a mathematical model for the calculation (forecasting) of the adhesion of a flame sprayed coating of powdered aluminum on S 235 JR steel. Experimental work was conducted according to a fractional central-composite design at three levels. The adhesion of the coatings made with combinations of input parameters of the procedure according to the experiment plan mentioned is measured in line with the EN 582 standard. A mathematical model was derived describing the dependence of the experimentally obtained adhesion values on the input parameters of the procedure. The possibility of analyzing the influence of the parameters on the adhesion for a certain combination of input parameters has been presented with the use of perturbation plots.     

A case study on the object-oriented framework for modeling product families with the dominant variation of the topology in the one-of-a-kind production

Traditional configuration-based product family modeling techniques do not yield favorable solutions for modeling the product families with the dominant product topology variations. This paper presents the case study for the modeling of variations of the product configuration, parameters, and topologies in mass production of custom windows and doors in a one-of-a-kind production (OKP) company. The case study is based on the object-oriented product family modeling framework we developed for OKP which is characterized by the dominant product variation by topology. The problem of variation in topology in our framework is solved by the manual model transformation in the computer-aided design module which creates a new metamodel of products with the desired topology and which is the basis for a further, automatic model transformation. Usage of our framework has a positive effect on the level of the product customizations and shortening of the leading time which helps OKP companies in obtaining a better position at the market. Our software solution for the designing and manufacturing of custom windows and doors based on our framework is implemented in more than 300 mostly small- and medium-sized enterprises. It proves our concept which can be used for the realization of the information systems for computer-aided one-of-a-kind production in the companies with a different production plan.     

Aerodynamic design and analysis of a small-scale vertical axis wind turbine

Small-scale vertical axis wind turbines are regarded today as an attractive source of green energy, still insufficiently implemented and tested. This paper presents a fast design methodology of such a VAWT, in terms of choosing its main parameters: airfoil, rotor diameter and solidity. For obtaining generated power of each considered geometrical model at different undisturbed wind velocities and rotor angular velocities two models were used — momentum and vortex-wake model, combined with experimentally measured airfoil data (airfoil lift and drag coefficients). Even though the former model is simpler, it is the most utilized model, known to provide good results in stationary working regimes. Both models still present fairly accurate and fast tools for computation and optimization, particularly useful in the phase of conceptual design. In this research, the use of the momentum model resulted in determination of the maximal power coefficient, optimal- and minimal freestream velocity for every considered VAWT model. From these output parameters, a selection of the optimal geometric model was done, and a more detailed transient analysis and flow representation around the selected solution was obtained by the vortex-wake model. The results obtained by the two used computational models coincide satisfactorily.