A dynamic system model for development challenges in Cameroon

Dynamic modeling of spindle bearing system and vibration response investigation

Dynamic performance of an organic Rankine cycle system with a dynamic turbine model: A comparison study

In some rural areas in the northwest of China, people are suffering from not only the voltage drop due to long distance transmission but also the power outages due to remoteness and poorly maintained grid. In recent few years, the price of solar energy has been reduced drastically every year in China due to the government policy on renewable energy. In the near future, isolated hybrid power systems for home use could be affordable and used by residences in these rural areas. Thus, it is necessary to design a hybrid power system based on local load and weather condition to check system feasibility and expected performance. It includes load simulation, system sizing, and dynamic system modeling and simulation. This paper firstly introduces current development of renewable energy in China and then goes through the sizing, modeling, and simulation of the system design for a typical remote home in China and finally discusses the system’s availability based on the simulation results. In this paper, the NASA website is the source for weather data, and BEopt is used to generate load data. During system modeling, the MPPT algorithm is much simpler designed than the complex incremental method. A soft starter is adopted with the diesel generator for stability. The charge controller of the battery storage provides external command to the MPPT and diesel PID controller to prevent the battery storage from overcharging. The rms value of the fundamental load voltage is used in the voltage control loop of the inverter.

This paper puts forward new dynamic model and control strategy of auto-leveling system for vehicle-borne platform with four legs. The new dynamic model for legs is built based on the method of linear graph. Through analyzing the dynamic model, the state space equations of the leveling system can be carried out. Aiming at the shortcomings of traditional leveling strategy, the new circular leveling strategy is applied in the leveling system to optimize the dynamic performance in the progress of auto-leveling. The test proves that the new leveling strategy improves the key factors of the leveling system: leveling-precision and leveling-time.

Method, information technology, computational algorithms and software tools for constructing a nonparametric dynamic model of the human oculomotor system were proposed. A method for constructing the nonparametric dynamic model of the human oculomotor system with regard to its inertia and nonlinear properties based on the data of experimental studies input-output, as well as efficient computational algorithms and software tools for processing the data of identification experiments were developed. Nonparametric nonlinear dynamic model of the oculomotor system based on processing the data of experiment input-output - pupillary response to a disturbance in the form of a light spot was obtained. Using the algorithms for intelligent processing of the captured video sequence of the pupil position change, the function of the oculomotor system response to a disturbance is simulated. Description of the oculomotor system properties is made using the most versatile nonlinear nonparametric dynamic models in the form of Volterra series. The technology for tracking the pupil behavior using the video recording, which has allowed to determine the dynamic characteristics of the oculomotor system according to the observational data input-output have got further development. The proposed technology for tracking the pupil behavior is available for widespread use in modern applications with an expanded set of personalized features, such as medical and athletic training machines, authorized access to data, testing human-machine systems and so on. An important feature of the technology is indiscriminateness to the hardware that allows its use in the applications of modern mobile devices.

Climate-change-based global sea-level rise is of concern because it contributes to significant loss of coastal wetlands and mangroves and to increasing damage from coastal flooding in many regions of the world. Physical mechanisms that describe the dynamic global climate systems and the effect of this system behavior on sea-level rise are inherently complex. In this study, conducted using systematic analysis of historic data on temperature change and sea-level rise, a linear dynamic system model is proposed to predict global sea-level rise and mean surface temperatures. Unlike the semiempirical approaches proposed in the recent literature, this model incorporates the inherent interaction between temperature and sea-level rise into the model. The resulting model, recognized from the historic data, shows that the rate of sea-level rise is proportional to temperature, and this rise is also a function of the temporal state of the sea level. Similarly, the rate of temperature change is a function of the temporal state of the temperature and is also affected by the sea-level rise. The proposed model is also used to predict the sea-level rise during the 21st century. DOI: 10.1061/(ASCE)HE.1943-5584.0000447. © 2012 American Society of Civil Engineers. CE Database subject headings: Climate change; Sea level; Temperature effects; Dynamic models; Predictions. Author keywords: Climate change; Complex systems; Sea-level rise; Temperature change; Dynamic model.

Chapter 11 - Trade-Offs Between Biodiversity Conservation and Nutrients Removal in Wetlands of Arid Intensive Agricultural Basins: The Mar Menor Case, Spain

Construction of a multipurpose water reservoir is certainly to enhance the welfare of a region. However more often than not, construction of the reservoir involves extensive area inundated on the upstream side resulting in imbalance on the socio-economic front of the surrounding urban areas. Consequently a great deal of efforts are needed to correct the imbalances created. The objective of this paper is therefore to establish the analytical framework to formulate the regional dynamic model involving the major impacts and the regional performance levels on the living environment.The following are the principal components of the study considered for detail investigation:(1) Formulation of a comprehensive framework of development promotion alternatives with the consideration for individual development measures and their synthesis with the overall dynamic model.(2) Evaluation of standards on the living environment in relation to the regional activities.(3) Examination of the evaluated standards for perspective changes during and after the reservoir construction.(4) Determination of priorities among alternatives based on the inhabitant's preference for improvement of their social environment.The study procedure is as follows:(1) The impact components and the performance levels on social environment in consonant with the development promotion measure for the upstream area are established by the “Nominal Group Technique”.(2) Basic scenarios and alternatives are built from the established facts in (1)above and specific policy framework is formulated.(3) The dynamic system model is built using the technique of “System Dynamics” to clarify the interrelationship between the development promotion projects and the performance level indices.(4) Several simulation are performed using the various alternative inputs.(5) The performance level of these indices are evaluated using the “Multicriteria Analysis” for every phase of the project.Application of the techniques mentioned above to the actual situation on the midstream of the Sorachi River in Hokkaido thruoghout the following results:(1) The regional employment potential could increase to 4.5% during the phase of dam consruction and drop to less than 1% increase on application of regional economic promotional measure.(2) By using each alternative the performance level of every living environmental facility could increase in proportion to the progress in the construction of the dam. In particular, the recreation facilities and medical facilities show greater increase.(3) In the case of evaluation of alternatives, it was found that regional economic promotional measures were the most appropriate for the inhabitant's needs and infrastructure facilities promotion was the second best.(4) The propposed analytical approach is considered to be the most appropriate to identify the complete system of a river basin and the region and decide the priority among the various development promotion measures.

Vibration-based updating of wear prediction for spur gears

So far, most of the proton exchange membrane fuel cell (PEMFC) models are difficult to apply in the control system design. In this paper, a dynamic control model of PEMFC system is set up. Based on this model, a self-adaptive fuzzy PID controller and a PID controller are respectively used to control the output voltage. The simulation results show that, this adaptive fuzzy PID controller can control the output characteristics more effectively than the PID controller, which can ensure PEMFC operate stably.

With the large-scale grid connection of renewable energy and the surge of peak power system demand, liquid carbon dioxide energy storage technology has become a research hotspot due to its high energy density and environmental friendliness. However, most of the existing research focuses on the steady-state performance of the system, and the parameter coupling and transient response characteristics under dynamic operating conditions are not yet clear. To this end, this paper constructs a dynamic simulation model of a 10 MW-class liquid carbon dioxide energy storage (LCES) based on the Simulink platform, focuses on the coupling effects of the compressor inlet temperature, pressure, and mass flow rate and the expander inlet mass flow rate on the system parameters, and reveals the dynamic correlation between the system work and the state of charge value of the tank under the variable power working condition. The results show that the system’s round-trip efficiency (RTE) is 65.3% under design conditions, and the energy density reaches 34.79 kW·h·m−3. Perturbation analysis shows that when the compressor inlet temperature rises from 283.15 K to 303.15 K, the power consumption fluctuates in the range of 96.84% to 102.99% under design conditions. The inlet pressure perturbation (0.5~1.5 bar) will cause the power consumption of the compressor to change by 80.2%. In variable power operation, the state of charge value of the high-pressure liquid tank level in the energy storage stage rises from 0 to 84.89%, and the state of charge value of the high-pressure liquid tank level in the energy release stage decreases from 84.89% to 31.48%. The dynamic model proposed in this paper can accurately capture the transient response characteristics of the system and provide theoretical support for the optimization design and engineering application of LCES.

This paper addresses the problem of synthesizing in real time the motion of realistic virtual characters with a physics-based model from the analysis of human motion data. The synthesis is achieved by computing the motion equations of a dynamical model controlled by a sensory motor feedback loop with a non-parametric learning approach. The analysis is directly applied on end-effector trajectories captured from human motion. We have developed a Dynamic Programming Piecewise Linear Approximation model (DPPLA) that generates the discretization of these 3D Cartesian trajectories. The DPPLA algorithm leads to the identification of discrete target-patterns that constitute an adaptive sampling of the initial end-point trajectory. These sequences of samples non uniformly distributed along the trajectory are used as input of our sensory motor system. The synthesis of motion is illustrated on a dynamical model of a hand-arm system, each arm being represented by seven degrees of freedom. We show that the algorithm works on multi-dimensional variables and reduces the information flow at the command level with a good compression rate, thus providing a technique for motion data indexing and retrieval. Furthermore, the adaptive sampling seems to be correlated with some invariant law of human motion.KeywordsCompression RateAdaptive SamplingSensory MotorProportional Integrative Derivative ControllerMotion Capture DataThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Hybrid actuators can provide better performances than hydraulic or electromechanical actuators alone; however, control of these hybrid systems is more challenging. This paper presents the application of model predictive control (MPC) on a hybrid actuator system to coordinate multiple control objectives. MPC has advantages over traditional controllers such as a PID in controlling non-linear multi-input, multi-output systems. MPC proactively updates the control inputs in a specific time interval by observing the current state of the system, predicting the future behavior, and solving an optimization problem repeatedly with consideration of pre-defined control objectives. In this paper, a high-fidelity dynamic model of the hybrid actuator system will be developed and a simplified, reduced-order model will be derived for use in the MPC formulation process. The detailed process of designing an MPC controller, which may consist of mathematical formulation of an optimization problem and numerical methods to find the optimal solution, will be discussed in detail. Simulation results will be presented to compare the performances of the MPC with PID controllers, and the effects of different controller parameters on the system performances will be discussed.

A dynamic simulation model of a hybrid power generation system of a solid oxide fuel cell and a homogeneous charge compression ignition engine was developed to investigate the behavior of the system during the start-up process. The stack, reformer, catalytic burner, and heat exchanger were implemented as dynamic models based on physical equations. For the engine, an experimental data-based mapping model was developed. The dynamic model was simulated on a Matlab/Simulink platform. Individually developed component models were assembled as an integrated system model and operated at the system level. The hybrid system was designed to generate approximately 4 kW of electricity from the SOFC stack and 1 kW from the engine, resulting in a total system power of 5 kW, with an electrical efficiency of 50.6%. The integrated model was operated using a four-step start-up procedure for 50 h, during which the temperature and composition of the stream were observed in time. Based on this, the dynamic behavior of the system was analyzed at each stage throughout the entire start-up process from ambient to high operating temperature. Validation of key results suggests a close resemblance between the model and an actual system. Therefore, the proposed model is expected to exceed the limitations of the existing static model analysis method.

Failure analysis of reciprocating compressor crankshafts