In this research, a one-dimensional heterogeneous model is developed to simulate the partial oxidation of methanol to formaldehyde over a molybdenum-iron catalyst in an industrial isothermal reactor at dynamic conditi...
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In this research, a one-dimensional heterogeneous model is developed to simulate the partial oxidation of methanol to formaldehyde over a molybdenum-iron catalyst in an industrial isothermal reactor at dynamic condition. The considered isothermal reactor is modelled based on the mass and energy balance equations considering catalyst deactivation. Based on the simulation results, decline in the catalyst activity from 1.0 to 0.73 decreases the rate of formaldehyde production rate from 94.9 kmol h-1 to 89.63 kmol h-1 during process run time. Subsequently, a multi-objective optimization problem is programmed to enhance formaldehyde productivity and minimize the production decline during process run time. To select the effective decision variables, a sensitivity analysis is performed based on the developed dynamic model. Then, the programmed multi-objective optimization problem is replaced with a single objective by the weighted sum method, and the problem is handled by the genetic algorithm method to determine the optimal trajectory of coolant temperature. The simulation results showed that the average formaldehyde production rate increases from 92.11 kmol h-1 to 95.22 kmol h-1 when the optimal conditions are applied to the reactor.
The proceedings contain 64 papers. The topics discussed include: simulation study of reliability model and optimization for electrical power system;simulated analysis of liquid system for high-power power electronic e...
The proceedings contain 64 papers. The topics discussed include: simulation study of reliability model and optimization for electrical power system;simulated analysis of liquid system for high-power power electronic equipment;modeling and investigation of the reduction zone in a downdraft biomass gasifier;modeling of direct drive wind turbine for wide-band oscillation analysis in large power grid;an improved model for predicting the trapped annular pressure in the deepwater's annulus containing foam material;research on target imaging scene simulation for photoelectronic tracking;design, modeling and motion simulation of a setback arming mechanism under weak acting forces;design and simulation analysis of wide-range current transformer with adaptively adjustable air gap length;and simulation and optimization design for energy absorption characteristics of multi-cell thin-walled structures.
The proceedings contain 89 papers. The topics discussed include: research on modeling and simulation technology of equipment maintenance support system based on agent;kinematics and simulation analysis of longitudinal...
The proceedings contain 89 papers. The topics discussed include: research on modeling and simulation technology of equipment maintenance support system based on agent;kinematics and simulation analysis of longitudinal-torsional ultrasonic assisted grinding of zirconia ceramics;intelligent evaluation method of marine engine simulator based on combination weighting;application of uncertainty analysis in evaluation of marine engine simulator;research on an anechoic wind tunnel in the design phase by numerical simulation;resource allocation for cloud-edge-end simulation system;optical simulations on the surface plasmon polaritons loss & power dissipation in organic light emitting diodes;simulation and design of rising-sun anode blocks for magnetrons with two outputs of energy;and agile modeling and simulation technology of heterogeneous systems based on meta-model modeling method.
Multiobjective building design optimization is a challenging problem because it involves finding a set of solutions that simultaneously optimize multiple conflicting objectives. simulations-based optimization is widel...
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Multiobjective building design optimization is a challenging problem because it involves finding a set of solutions that simultaneously optimize multiple conflicting objectives. simulations-based optimization is widely used, but it is a computationally expensive process in terms of time, as it requires a large number of evaluations of the objective functions. Metamodel-based optimization is an alternative to reduce the time-consuming simulations during the optimization process. Metamodels can approximate the building simulation model with analytical expressions. However, the accuracy of metamodels depends on the number of simulations used to train the model and the sampling strategy used to select informative samples over the design space. This study proposes an efficient sequential sampling approach to fit the metamodels toward the regions of the design space where their accuracy is higher and can improve all objectives simultaneously. To demonstrate the effectiveness of this approach, it was applied to optimize the energy and investment costs of a multi-story residential building. The optimization results were compared with those obtained using a non-dominated sorted genetic algorithm II (NSGA-II). The results of this study show that the proposed method reduces the number of building energy simulations required by up to 50% while guaranteeing accurate optimization results. Fifteen energy-efficient buildings designs were proposed, with a wide range of trade-offs between energy and investment costs. This study highlights the potential of the proposed approach to achieve faster and accurate building design optimization and allowing for a larger design space, leading to more creative and innovative solutions.
The proceedings contain 90 papers. The topics discussed include: modeling analysis of carrier-based aircraft's scheduling on flight deck;modeling on heterosynaptic plasticity based on postsynaptic membrane potenti...
The proceedings contain 90 papers. The topics discussed include: modeling analysis of carrier-based aircraft's scheduling on flight deck;modeling on heterosynaptic plasticity based on postsynaptic membrane potential and current density;classification and quantitative modeling analysis of groundwater hardness based on ultraviolet absorption spectrum;congestion control of multi-layer cellular networks based on modeling of transmit power;an evaluation method of dc magnetic bias vibration for transformer based on prior knowledge and neural network modeling;simulation and functional mechanism of tuna median fins on yaw mobility in unsteady flow;modeling and intelligent identification of axis orbit for rotating machinery based on the convolution neural networks;and modeling and robust continuous power allocation strategy with imperfect channel state information in cognitive radio networks.
The proceedings contain 61 papers. The special focus in this conference is on modeling, simulation and optimization. The topics include: Combined Crack and Unbalance Response simulation for a Spinning Rotor;stability ...
ISBN:
(纸本)9789811598289
The proceedings contain 61 papers. The special focus in this conference is on modeling, simulation and optimization. The topics include: Combined Crack and Unbalance Response simulation for a Spinning Rotor;stability of Female Bicyclists on Sudden Braking;stability of Bicycle at Low Speed;impact of Helical Coil Insert in the Absorber Tube of Parabolic Trough Collector;integral-Tilt-Derivative Controller Based Performance Evaluation of Load Frequency Control of Deregulated Power System;six Sigma Enablers for Incoming Material Quality Improvement and Their Interaction in Supplier Domain for Indian Manufacturing Scenario;MLGARTC: Machine Learning Based Genetic Approach in RSSI Tree Climbing Path Improvisation of the Mobile Anchor’s Using K-Means Clustering of Wireless Sensor Network;modeling Performance and Power on Disparate Platforms Using Transfer Learning with Machine Learning Models;A Novel Effective Single Sensor MPPT Technique for a Uniform and Partially Shaded Solar PV System via MSCA Approach;thermal Performance Study of Bamboo and Coal Co-gasification in a Downdraft Gasifier;Classification of Sequence Data Using LSTM: An Application on Chaotic Sequences;modeling and simulation of a Multi-area Hydro-thermal Interconnected System Using FOPIµ Controller for Integrated Voltage and Frequency Control;dye Sensitized Solar Cell Parameter Extraction Using Particle Swarm optimization;modeling and simulation of an Isolated CCGT and DSTS Plant Using BWO Optimized PIλDμ Controller for Amalgamated Control of Voltage and Frequency;mathematical Analysis on the Behaviour of Tumor Cells in the Presence of Monoclonal Antibodies Drug;LFC of a Solar Thermal Integrated Thermal System Considering CSO Optimized TI-DN Controller;simulation and Behavior of Vertically Oriented Planar Structure.
The channel layouts on bipolar interconnects play an important role in improving the electrochemical performance of solid oxide fuel cells (SOFCs). Most previous layout design studies are performed based on artificial...
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The channel layouts on bipolar interconnects play an important role in improving the electrochemical performance of solid oxide fuel cells (SOFCs). Most previous layout design studies are performed based on artificial predetermination without optimization. In this study, a topology optimization method for the flow channel layout of SOFCs based on the real microstructure of SOFC components is presented. Based on the reconstructed real microstructure, relevant numerical simulations are performed to analyze the multiphysics coupling mechanisms in SOFCs and provide an effective tool for SOFC performance prediction. To further improve SOFC performance, a numerical framework for flow field optimization based on the actual microstructure of a specific SOFC is proposed. The density-based topology optimization is used for the layout of the flow channels by coupling it with the multiphysical fields generated from electrochemical simulation coupled with flow field modeling. The optimization is modified based on the modification of the source term derived from the electrochemical simulation to achieve a significant improvement in the electrochemical performance of the SOFCs.
With the increasing adoption of self-service bag drop facilities, modern airports necessitate check-in counter optimization models that strategically allocate passengers between staffed and self-service facilities whi...
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With the increasing adoption of self-service bag drop facilities, modern airports necessitate check-in counter optimization models that strategically allocate passengers between staffed and self-service facilities while balancing operational costs and service quality. This study develops a two-tiered decision framework integrating dynamic integer programming and discrete-event simulation (DES) to minimize manual counter-staffing costs while guaranteeing service level agreements. We first formulate an integer programming model that allocates passengers to manual or self-service channels based on passengers' profiles. To address queue overflow during peak hours, a dynamic capacity scaling factor is introduced to the integer programming model. The DES module then iteratively validates queueing dynamics and feeds back queueing time to optimization layer, triggering increase in the capacity scaling factor and reallocations when predicted wait times exceed 15-min thresholds. applied to Baiyun Airport Terminal 2, the model results show a 9.2% increase in operational cost (from 8824.5 to 9633.75) but a 30.9% reduction in average manual check-in wait time (from 8.1 to 5.6 min), reducing peak-period congestion. This study provides decision support for optimizing check-in counter operations at airports.
The proceedings contain 48 papers. The topics discussed include: research on distributed target assignment based on dynamic allocation auction algorithm;research on target assignment method based on ant colony-fish gr...
The proceedings contain 48 papers. The topics discussed include: research on distributed target assignment based on dynamic allocation auction algorithm;research on target assignment method based on ant colony-fish group algorithm;research on netizens' emotion evolution in emergency based on machine learning;application of multi-variable grey model method in power load forecasting;assessment of environmental degradation costs: a case study of beijing and tianze agricultural parks;image registration of infrared and visible image based on geometric constraint;a high-speed serial digital interface video signal jitter measurement method;and a low complexity robust adaptive beamforming method with orthogonality constraint.
Given the urgent need to mitigate increasing CO2 emissions and alleviate the climate crisis, amine-based post-combustion capture (PCC) processes have emerged as a prominent method to reduce the emissions from industri...
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Given the urgent need to mitigate increasing CO2 emissions and alleviate the climate crisis, amine-based post-combustion capture (PCC) processes have emerged as a prominent method to reduce the emissions from industrial point sources. While many technological advancements have been introduced for such processes, leading to decreased energy requirements for capture, there are still only a few commercial installations because of their high costs. Therefore, these processes can benefit from process optimization to enhance their economic viability. This work presents anew open-source, rate-based, equation-oriented model of a novel PCC process that uses piperazine as the amine solvent. The model was implemented in Python, in accordance with the Pyomo-based IDAES modeling and optimization framework. The proposed nonlinear model can be used for both simulation and optimization. To ensure its robust convergence, we further devise a rigorous, multi-level cascade initialization scheme, whose principles can further be applied towards the initialization of similar process models. The model was validated with published pilot plant data and then optimized for pilot and commercial scales with an economic objective that considers both capital and operational costs. Results show that process optimization can indeed improve the economics of this technology, leading to 15.6% yearly savings at the pilot scale compared to the baseline case considered in the study. Additional parametric analyses were performed to understand how the flue gas flowrate and CO2 concentration, as well as the target capture rate, affects the cost of capture.
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