In this work, is developing a method for obtaining the point of impact of a rocket by telemetry data and a Slant Range device. The trajectory data was obtained from a real flight path by merging the angular components...
详细信息
In this paper autotuning and self-tuning methods for Dynamic Matrix Control (DMC) are presented with application to single-input single-output (SISO) processes which can be approximated by a first-order-plus-dead-time...
详细信息
In this paper autotuning and self-tuning methods for Dynamic Matrix Control (DMC) are presented with application to single-input single-output (SISO) processes which can be approximated by a first-order-plus-dead-time model. In order to validate the method a nonlinear control valve system described by a Wiener process is simulated. This process was identified by a Hammerstein model and controlled by DMC with output compensator. The proposed tuning methods have its performance compared to another standard method found in literature, showing more conservative results regarding smoothness of the control action while maintaining adequate performance on set-point tracking.
This article delves into the significance of urban digital twins in generating synthetic data specifically tailored for individuals with disabilities. It explores how this data can be effectively utilized to construct...
详细信息
Injection Molding (IM) is considered to be the most important process for mass-producing plastic products. One of the biggest challenges facing injection molders is to determine the best settings for the controllable ...
详细信息
ISBN:
(纸本)1887706372
Injection Molding (IM) is considered to be the most important process for mass-producing plastic products. One of the biggest challenges facing injection molders is to determine the best settings for the controllable process variables (CPVs). Selecting the proper settings is crucial because the behavior of the polymeric material during shaping is highly influenced by the process variables. The difficulty of optimizing an IM process is that the performance measures (PMs), such as surface quality or cycle time that characterize the adequacy of the part for its intended purpose usually show conflicting behavior. Furthermore, in actual molding, the CPVs will vary over some range during molding. This inconsistency of the process variables will lead to variability in the PMs. In high precision manufacturing, in particular for micro and nano scale components and devices, this variability needs to be minimized, and if possible eliminated. Thus, the variability in the PMs needs to be included in the optimization problem. The aim of this work is to demonstrate a method based on CAE, statistical testing, artificial neural networks (ANNs), and data envelopment analysis (DEA) to find the optimal compromises between multiple PMs and their variability to prescribe the values for the CPVs in IM. We present an example where the optimization is carried out in two phases. Phase one uses the PMs that are significantly affected by the injection gate location in order to prescribe two possible injection gates. Phase two of the optimization uses Data Envelopment Analysis (DEA) to find a PM-based efficient frontier for each injection gate considering process variability. These two efficient frontiers are then compared to select the best location. Other possible applications are discussed.
In competitive segments like automobile and bus manufacturing industries, quality of vehicles need to be improved constantly to meet internal and external market demands. Compliance with international standard regulat...
详细信息
This working-in-progress paper aims to present a three-dimensional reconstruction using aerial images in different environments. The experiments were conducted with aircraft in both external and internal settings, sta...
详细信息
Human identification both prior to death and after death is becoming one of the major worldwide issues nowadays for law enforcement aspect as well as social and security aspects. General identification prior to death ...
详细信息
ISBN:
(纸本)9789881404732
Human identification both prior to death and after death is becoming one of the major worldwide issues nowadays for law enforcement aspect as well as social and security aspects. General identification prior to death is possible through comparison of many biometric identifiers. However identification after death is impossible using behavioral biometric such as speech and actions. Moreover, in many circumstances such as natural disasters, air plane crash or a case of identification a couple of weeks later, most of physical biometrics may not be useful for identification due to the decay of some soft tissues. A lot of research has been done in the field of different biometric modalities like Finger-print, Iris, Hand-Veins, Dental biometrics etc. to identify humans. However only a little has been known the chest X-Ray biometric which was very powerful method for identification especially during the mass disasters in which most of other biometrics are unidentifiable. Therefore in this paper, we propose a stochastic modelling approach for human identification after death by using chest X- Ray prior to death database. Some experimental results are shown based on real life dataset and confirmed.
The objective of this work is to compare the augmented neural network (AugNN) metaheuristic to minimum bin slack (MBS) heuristic to solve combinatorial optimisation problems, specifically, in this case, the one-dimens...
详细信息
作者:
Lecourt, EJE.J. Lecourt
Jr. is a graduate of the USCG Academy. Received MS degrees from MIT in Electrical Engineering and Naval Architecture and Marine Engineering. Currently Program Manager at PDI Division of Bird-Johnson Companey. Forty years experience in research design analysis and testing of marine engineering systems with perarticular emphasis on electric propulsion systems. While in the USCG served two years aboard a turbo-electric ship and two years aboard a diesel-electric ship. Member ASNE and SNAME.
The WAGB-20 is a U. S. Coast Guard polar icebreaker with an integrated diesel-electric propulsion system. Power is generated by four main diesel engines driving AC generators. Two main 15,000-HP AC synchronous propuls...
详细信息
The WAGB-20 is a U. S. Coast Guard polar icebreaker with an integrated diesel-electric propulsion system. Power is generated by four main diesel engines driving AC generators. Two main 15,000-HP AC synchronous propulsion motors are directly coupled to the port and starboard propellers. Two cycloconverters provide variable-voltage, variable-frequency power for controlling each propulsion motor. The simulation of the electric propulsion system is being developed to analyze the steady-state and transient performance of the system during open water and icebreaking operations. The objectives of the analysis are to support propulsion plant design, aid in the integration of system components, develop control system algorithms, predict system performance, and determine the requirements for dynamic braking resistors. The analysis consists of mathematical models for the ship, shaft systems, propellers, AC synchronous propulsion motors, motor controllers, cycloconverters, generators, generator exciters, voltage regulators, diesel engines, and engine governors. These models are based on actual machinery data. The WAGB-20 specification requires the propulsion system to have the capability of going from full power ahead to full power astern in open water in 25 seconds or less. This paper presents the simulation results which show that by controlling the regenerative power the crash astern maneuver can be performed to meet this requirement without the need for dynamic braking resistors.
作者:
Suelen GasparinJulien BergerDenys DutykhNathan MendesThermal Systems Laboratory
Mechanical Engineering Graduate Program Pontifical Catholic University of Paraná Rua Imaculada Concei??o 1155 Curitiba - Paraná 80215-901 Brazil LAMA
UMR 5127 CNRS Université Savoie Mont Blanc Campus Scientifique 73376 Le Bourget-du-Lac Cedex France Université Savoie Mont Blanc
CNRS LOCIE F-73000 Chambéry France LAMA
UMR 5127 CNRS Université Savoie Mont Blanc Campus Scientifique 73376 Le Bourget-du-Lac Cedex France Thermal Systems Laboratory
Mechanical Engineering Graduate Program Pontifical Catholic University of Paraná Rua Imaculada Concei??o 1155 Curitiba - Paraná 80215-901 Brazil
Implicit schemes require important sub-iterations when dealing with highly nonlinear problems such as the combined heat and moisture transfer through porous building elements. The computational cost rises significantl...
详细信息
Implicit schemes require important sub-iterations when dealing with highly nonlinear problems such as the combined heat and moisture transfer through porous building elements. The computational cost rises significantly when the whole-building is simulated, especially when there is important coupling among the building elements themselves with neighbouring zones and with HVAC (heating ventilation and air conditioning) systems. On the other hand, the classical Euler explicit scheme is generally not used because its stability condition imposes very fine time discretisation. Hence, this paper explores the use of an improved explicit approach—the DuFort–Frankel scheme—to overcome the disadvantage of the classical explicit one and to bring benefits that cannot be obtained by implicit methods. The DuFort–Frankel approach is first compared to the classical Euler implicit and explicit schemes to compute the solution of nonlinear heat and moisture transfer through porous materials. Then, the analysis of the DuFort–Frankel unconditionally stable explicit scheme is extended to the coupled heat and moisture balances on the scale of a one- and a two-zone building models. The DuFort–Frankel scheme has the benefits of being unconditionally stable, second-order accurate in time O(Δt2) and to compute explicitly the solution at each time step, avoiding costly sub-iterations. This approach may reduce the computational cost by twenty as wel as it may enable perfect synchronism for whole-building simulation and co-simulation.
暂无评论