Reliable Simulation Model Research Articles

Review on applications of artificial intelligence methods for dam and reservoir-hydro-environment models

Efficacious operation for dam and reservoir system could guarantee not only a defenselessness policy against natural hazard but also identify rule to meet the water demand. Successful operation of dam and reservoir systems to ensure optimal use of water resources could be unattainable without accurate and reliable simulation models. According to the highly stochastic nature of hydrologic parameters, developing accurate predictive model that efficiently mimic such a complex pattern is an increasing domain of research. During the last two decades, artificial intelligence (AI) techniques have been significantly utilized for attaining a robust modeling to handle different stochastic hydrological parameters. AI techniques have also shown considerable progress in finding optimal rules for reservoir operation. This review research explores the history of developing AI in reservoir inflow forecasting and prediction of evaporation from a reservoir as the major components of the reservoir simulation. In addition, critical assessment of the advantages and disadvantages of integrated AI simulation methods with optimization methods has been reported. Future research on the potential of utilizing new innovative methods based AI techniques for reservoir simulation and optimization models have also been discussed. Finally, proposal for the new mathematical procedure to accomplish the realistic evaluation of the whole optimization model performance (reliability, resilience, and vulnerability indices) has been recommended.

Simulation of Grouting Process in Rock Masses Under a Dam Foundation Characterized by a 3D Fracture Network

Grouting plays a crucial role in dam safety. Due to the concealment of grouting activities, complexity of fracture distribution in rock masses and rheological properties of cement grout, it is difficult to analyze the effects of grouting. In this paper, a computational fluid dynamics (CFD) simulation approach of dam foundation grouting based on a 3D fracture network model is proposed. In this approach, the 3D fracture network model, which is based on an improved bootstrap sampling method and established by VisualGeo software, can provide a reliable and accurate geometric model for CFD simulation of dam foundation grouting. Based on the model, a CFD simulation is performed, in which the Papanastasiou regularized model is used to express the grout rheological properties, and the volume of fluid technique is utilized to capture the grout fronts. Two sets of tests are performed to verify the effectiveness of the Papanastasiou regularized model. When applying the CFD simulation approach for dam foundation grouting, three technical issues can be solved: (1) collapsing potential of the fracture samples, (2) inconsistencies in the geometric model in actual fractures under complex geological conditions, and (3) inappropriate method of characterizing the rheological properties of cement grout. The applicability of the proposed approach is demonstrated by an illustrative case study—a hydropower station dam foundation in southwestern China.

Modular optimized data assimilation and support vector machine for hydrologic modeling

Abstract Accurate and reliable simulation models are crucial for the operation and management of systems. Developing a simulation model to forecast future states of a system is generally followed by errors in prediction. Frequently, data-based models such as support vector machines (SVM) are used as forecasting techniques. This paper introduces a modular method which couples the machine learning technique of support vector regression (SVR) as a prediction model and a modified data assimilation (MDA) technique to partially correct the predicted values based on the observation data. To improve the performance and accuracy of the system output, the ensemble Kalman filter (EnKF) as a data assimilation procedure is implemented with an optimization procedure. As a case study, inflow quantities to Zayandehroud reservoir is considered as the state vector in the assimilation process to enhance the system output. Evaluation criteria such as root mean square error (RMSE) and R-squared criteria are implemented to evaluate the performance of the proposed model. The adjusted values of a hybrid model compared to the SVR model and standard DA indicate improved performance of the proposed model.

Calibration and validation of large-scale traffic simulation networks: a case study

The availability, accuracy and relevance of real world input data are essential for developing a reliable traffic simulation model. Large-scale traffic simulation models, in particular, require data from many sources and in great detail. Though it is now possible to obtain detailed field data with the advent of new technologies such as GPS, cellular phones, RFIDs, it is still a challenge to gather all available data, especially traffic flow data, in the required spatial and temporal accuracy. The central theme of this paper is the calibration and validation (C&V) development of a large-scale traffic simulation model using data from multiple sources.

Optimisation of HF signal injection parameters for EV applications based on sensorless IPMSM drives

The study proposes a parameter optimisation of the high-frequency (HF) signal injection sensorless algorithm applied to an interior permanent magnet synchronous machine (IPMSM). The latter is intended for electric vehicle (EV) traction applications with dedicated mission profile under specific constraints. This optimisation aims to minimise two conflicting objectives: (i) minimising the position estimation error which impacts the torque accuracy and (ii) minimising torque ripples responsible for additional stress on the motor shaft, causing unwanted noise in the vehicle powertrain. The main contribution of this study is to provide guidelines for the selection of the HF signal injection tuning parameters so as to satisfy these objectives. To do so, a genetic algorithm has been implemented and the optimisation process is based on a reliable simulation model. Using a simulation model is deliberately chosen in order to reflect the behaviour of a motor series. Besides, in order to integrate the specificities of the target application, the optimisation process is based on a typical EV mission profile. A set of non-dominated solutions satisfying the tradeoff between the position error and the torque ripples is obtained, discussed and finally tested with success on an experimental setup.

From high-energy demands to nZEB: the retrofit of a school in Catalonia, Spain

Since existing buildings are responsible for almost 40% of the energy consumption, a major focus in the construction sector is represented by building energy-saving retrofits. Considering the limited current economic possibilities in the construction market, the retrofit of existing buildings has become a target for both private actors and public administrations in most of European countries. In this context, the province of Catalonia in Spain is defining strategic plans and guidelines to help energy retrofits according to nZEB criteria. In this framework, the present paper evaluates the effectiveness of a series of strategies considered in the energy refurbishment of a school located in the Metropolitan Area of Barcelona. Firstly, the study reports the results of an extensive (level three) energy audit. This data is then used to create a reliable energy simulation model. A set of possible interventions is hence investigated considering technical feasibility, cost, and potential energy saving and indoor comfort benefits. Results show the actual possibility of reaching the nZEB standard at the end of the refurbishment of this high-energy consuming building. Finally, the case study is discussed as a valuable example for promoting energy retrofits in Catalonia and beyond.

Aircraft test of engineered material arresting system

PurposeEngineered material arresting systems (EMASs) are dedicated to stopping aircraft that overrun the runway before they enter dangerous terrain. The system consists of low-strength foamed concretes. The core component of the arresting system design is a reliable simulation model. Aircraft test verification is required before the practical application of the model. This study aims to propose a simulation model for the arresting system design and conducts serial verification tests.Design/methodology/approachSix verification tests were conducted using a Boeing 737 aircraft. The aircraft was equipped with an extra inertia navigation system and a strain gauge system to measure its motion and the forces exerted on the landing gears. The heights of the arrestor beds for these tests were either 240 or 310 mm, and the entering speeds of the aircraft ranged from 23.9 to 60.6 knots.FindingsTest results revealed that both the aircraft and the pilots on board were safe after the tests. The maximum transient acceleration experienced by the dummies on board was 2.5 g, which is within the human tolerance. The model exhibited a satisfied accuracy to the field tests, as the calculation errors of the stopping distances were no greater than 7 per cent.Originality/valueThis study proposes a simulation model for the arresting system design and conducts serial verification tests. The model can be used in EMAS design.

An Overview of Crowd Evacuation Simulation

Emergency scenario is an unforeseen situation that threated human life. Emergency action plans comprising crowd evacuation is essential to prevent the occurrence of human injury and death. Therefore, this paper proposed a crowd evacuation simulation model to provide an effective and realistic approach in dealing with evacuation procedure during fire in a building. In order to build a reliable simulation model, this paper focuses on exploring the characteristics and significance of existing simulation models and techniques from the literature. Combination of Social Force Model (SFM) and Agent Based Simulation (ABS) technique has been chosen as the solution to realistically model fire emergency evacuation scenario. The proactive and independent characteristics of agents in both approaches will contribute to the good representation of actual fire scenarios in the crowd evacuation simulation

Effect of 45‐Day −6° Head‐Down Bed Rest on Cooperation and Aggression

SummaryHigh levels of cooperation and low aggression seem obviously vital to the successful implementation of space missions. To elucidate the effect of microgravity on these behaviors, we investigated whether cooperative and aggressive behaviors would be affected in 16 male volunteers during 45‐day −6° head‐down bed rest, which is a reliable simulation model for most physiological effects of spaceflight. We used an ultimatum game task to evaluate the cooperative behavior and a revised competitive reaction time test to evaluate the aggressive behavior simultaneously. We found that (1) the participants became less cooperative in the post‐bed rest phase in comparison with the pre‐bed rest phase and (2) the participants became more aggressive in the in‐bed rest phase in comparison with the pre‐bed rest phase. These findings provide evidence that head‐down bed rest may affect both cooperative and aggressive behaviors in males, suggesting an important perspective for future studies in space psychology.Copyright © 2017 John Wiley & Sons, Ltd.

Visualized strategy for predicting buildings energy consumption during early design stage using parametric analysis

Recently, there has been a high level of demand for sustainable design of buildings construction. The catalysts for such demand are rising energy costs and increasing environmental concerns. Therefore, it is important to evaluate building energy consumption, which is the key problem of building energy saving. There is a need for a reliable energy simulation model to predict buildings energy consumption. In addition, designers suffer from the limitations of energy simulation tools during the early design stage that addresses buildings envelope and orientation. This study proposes a strategy for visualized parametric energy analysis of buildings during the conceptual design phase. It presents an energy-oriented workflow that accommodates the Egyptian context. A residential building model is developed by coupling parametric analysis and building energy modeling tools as a means of developing an energy consumption database. The parallel coordinate plot is used to visualize the database to allow decision makers to flexibly evaluate energy performance. The advantages of this paper stem from: 1) providing a new strategy for visualizing the predicting building energy consumption data; 2) facilitating the process of decision making for energy design alternatives during early stages; 3) integrating parametric modeling and energy simulation engine in one platform to come over the problem of interoperability; 4) developing a generic model with variant energy simulation parameters; and 5) presenting an automated and simplified approach to enable modelers to simulate and analyze building energy performance with a more timely, accurate and efficient process.

Characterization and modeling of cooling and drying of pellets for animal feed

ABSTRACTThe process used to produce pellets for animal feed, especially the drying–cooling step, has not been extensively explored in the literature. However, with the increased industrial use of adjustable-speed drives to reduce fan energy consumption, the need for reliable simulation models has increased. In this work, different formulations of pellets were characterized and both their drying and drying–cooling kinetics were modeled. In comparing the results of the simulations with experimental results, the observed discrepancies were similar to the experimental uncertainties, indicating that our prediction tools yielded imperfect but acceptable results both in the thin-layer and deep-bed drying configurations. Furthermore, the approach centered on drying kinetics was also able to predict drying–cooling kinetics. This work suggests that one simple EMC equation, without temperature dependency, may correctly fit the behavior of several kinds of pellets and be sufficient for accurate simulations. The overall approach may be easily applied to many other kinds of pellets.

Energy performance analysis of STILE house at the Solar Decathlon 2015: Lessons learned

West Virginia University and University of Rome Tor Vergata have partnered for the Solar Decathlon 2015 to present STILE (Sustainable Technologies Integrated in a Learning Experience), a house that merges Italian and Appalachian design concepts with innovative energy techniques.The aim of the work is the construction of a reliable and accurate dynamic building simulation model to perform a posteriori critical analysis of energy performance of the STILE house during the competition and to investigate the capability of the same house during a typical year in different locations. This was possible through the calibration of a dynamic simulation model of the house, using data gathered during the contest in Irvine, USA in October 2015. The work helped us to better understand the problems faced and to find optimized solutions that did not alter the original architectural concept. A 17% saving in the HVAC energy consumption for the period of competition was obtained by acting on shading, windows materials, and adequate floor insulation. The same model was also used to evaluate STILE behavior in different climatic conditions for a typical year. The study shows that the house has satisfactory thermal performance with mild and temperate climates, or whenever a benefit can be obtained by the use of the solar chimney.

Development of Segmented Dynamic Combustion Model to Investigate Instability of Gas Turbine

This paper presents a dynamic combustion model with 10 segmented well-stirred reactors which thermo-acoustic instability of gas turbine is able to be evolved. Because combustion instability in gas turbine results in serious damage to the combustor system, it is inevitable to understand the physics of instability. In this study, segmented dynamic combustion model and thermo-acoustic instability model has been developed in Matlab/Simulink® platform. The dynamic segmented model is developed to understand the consumption of fuel and oxidizer and the volume segmentation is discretized by finite difference method. The thermo-acoustic instability model is based on the wave equation to describe the pressure fluctuation. Model is validated with reference experiment which shows that frequency of pressure appears 430Hz, 630Hz under the low-speed and high-speed range respectively. Also fluctuations of speed and temperature corresponding to the two input condition in the chamber were presented. As a result, reliable combustor simulation model has been developed to analyze combustion characteristics under the operating condition.

Capturing microscopic features of bone remodeling into a macroscopic model based on biological rationales of bone adaptation.

To understand Wolff's law, bone adaptation by remodeling at the cellular and tissue levels has been discussed extensively through experimental and simulation studies. For the clinical application of a bone remodeling simulation, it is significant to establish a macroscopic model that incorporates clarified microscopic mechanisms. In this study, we proposed novel macroscopic models based on the microscopic mechanism of osteocytic mechanosensing, in which the flow of fluid in the lacuno-canalicular porosity generated by fluid pressure gradients plays an important role, and theoretically evaluated the proposed models, taking biological rationales of bone adaptation into account. The proposed models were categorized into two groups according to whether the remodeling equilibrium state was defined globally or locally, i.e., the global or local uniformity models. Each remodeling stimulus in the proposed models was quantitatively evaluated through image-based finite element analyses of a swine cancellous bone, according to two introduced criteria associated with the trabecular volume and orientation at remodeling equilibrium based on biological rationales. The evaluation suggested that nonuniformity of the mean stress gradient in the local uniformity model, one of the proposed stimuli, has high validity. Furthermore, the adaptive potential of each stimulus was discussed based on spatial distribution of a remodeling stimulus on the trabecular surface. The theoretical consideration of a remodeling stimulus based on biological rationales of bone adaptation would contribute to the establishment of a clinically applicable and reliable simulation model of bone remodeling.

A cutting edge solution to monitor formation damage due to scale deposition: Application to oil recovery

AbstractOne of the detrimental issues in upstream oil industry is permeability impairment in oil reservoirs. The permeability may be reduced because of scale deposition originated from injected water incompatibility with the in‐situ water. To tackle this issue and monitor permeability impairment owing to scale deposition, an inventive evolutionary approach of Artificial Neural Network (ANN) is utilized which is based on the bio‐inspired science. This approach is optimized by various optimization algorithms which provide a high‐precision decision‐making process with low uncertainty associated with the interconnected weights of the developed neural network model. The constructed intelligent approaches are evaluated using extensive experimental data from the open literature. Moreover, two regression models are developed to highlight the robustness and precision of the addressed techniques. For model validation, the predictions obtained from the smart technique as well as the regression method are compared with the formation damage experimental data. Based on various performance criteria, it was obtained that the predictions from the optimized genetic algorithm have infinitesimal average relative and absolute deviation from the experimental data (< 0.1 %). The results obtained in the current research prove that implication of HGAPSO‐ANN in monitoring of formation damage associated with scale deposition in porous media results in reliable estimation of permeability impairment. This can result in designing a more reliable reservoir simulation model that captures the permeability impairment due to scale deposition, hence providing thorough action plans for developing EOR technologies that may cause scale deposition‐related formation damage.

A Novel Landing System to Increase Payload Capacity and Operational Availability of High Altitude Long Endurance UAVs

Unmanned stratospheric aircraft capable of staying aloft for long periods of time have become a topic of interest in the past years. Several problems are still to be solved to allow for a profitable commercial use of such aircraft. The inherent lightweight design leads to fragile structures with low payload capacities and a high wind sensitivity. The weather dependence significantly reduces the system’s operational availability. To address these drawbacks a novel landing system is proposed in this paper. The landing gear can be removed from the aircraft and a ground-based mobile landing platform is introduced. The main technical challenges consist in the precise relative state estimation and cooperative control of the involved vehicles. A reliable simulation model of the overall system was developed and a number of simulation experiments performed before the actual landing was attempted with an experimental system setup. Multiple successful landing experiments demonstrate the validity of the proposed system.

Investigation of Thermal Effect on Hot Forging Process of Yoke Flange by Finite Element Modeling

Finite Element Modeling (FEM) has been employed widely to analyze material flow behavior and identify potential defects in a hot forging process before try-out. Normally, the isothermal assumption should be used to simulate this process because the forming time was extremely shot around 0. 5 s – 1 s due to a high velocity of a press machine. However, in some cases when the contact pressure and contact area are extremely high, the heat could significantly dissipate to the forming dies. In case of Yoke flange simulation the isothermal condition could not be used to identify the defect as occurring in the real process. The forging defect (i.e. insufficient gap) was found at the apex of a workpiece in the rough or preform step. In this study, the non-isothermal assumption was used for investigating the defects. The forming process was divided in 3 steps; namely the transportation step when the billet was transferred from an induction furnace to the forging dies by conveyer, the rough forging and the finish forging steps. Temperatures, loads and gaps between workpiece and die at each step of the forming processes were measured and compared with the simulation results. For developing the reliable simulation model, the suitable heat transfer coefficients for each step would be determined. The heat transfer during the forming steps had an effect on the material flow and, the non-isothermal simulation model and could identify the insufficient gap in the rough step.

A Simulation Model for Industrial Multi-Channel Wireless Sensor Networks

The use of Wireless Sensor Networks (WSN) in industrial environments is subject to problems, such as shadowing and fading. In addition, the wireless channel in many industrial environments is non-stationary for a long term, which can cause abrupt changes in the characteristics of the channel over time. A way to deal with those problems is the use of multi-channel protocols. However, it is difficult to evaluate, and compare different approaches because there is no reliable simulation model for industrial environments. This paper presents experimental results that characterize the wireless channel in industrial environments, and proposes a simulation model that captures the effects of fading, shadowing, and the non-stationary characteristics of the channel. It also considers the differences in the behavior of the different channels, and the asymmetry of the links. The model was integrated into the open source simulator Castalia. After the integration, two simulation studies were performed with the proposed model. In the first one, the Tree-based Multi-Channel Protocol was implemented and evaluated, and a comparison was made with the default model from Castalia. In the second case, CSMA/CA protocol, as defined in IEEE 802.15.4 standard, was compared to a protocol based on Time-Slotted Channel Hopping (TSCH) mode of IEEE 802.15.4e standard. The results showed that the use of TDMA and channel hopping is an alternative to deal with the problems of wireless channels in industrial environments.

A cellular automaton simulation model for pedestrian and vehicle interaction behaviors at unsignalized mid-block crosswalks

At unsignalized crosswalks, interactions between pedestrians and vehicles often lead to traffic safety hazards due to absence of traffic control and unclear right-of-ways. To address this safety problem, there is a need to understand the interaction behaviors of pedestrians and vehicles that are complicated by a variety of traffic and roadway attributes. The prime objective of this study is to establish a reliable simulation model to represent the vehicle yielding and pedestrian crossing behaviors at unsignalized crosswalks in a realistic way. The model is calibrated with detailed behavioral data collected and extracted from field observations. The capability of the calibrated model in predicting the pedestrian-interaction events as well as estimating the driver yielding rate and pedestrian delay are also tested and demonstrated. Meanwhile, the traffic dynamics in the vicinity of the crosswalk can be meaningfully represented with simulation results based on the model. Moreover, with the definitions of the vehicle-pedestrian conflicts, the proposed model is capable to evaluate the pedestrian safety. Thereby, the simulation model has the potential to serve as a useful tool for assessing safety performance and traffic operations at existing facilities. Furthermore, the model can enable the evaluation of policy effectiveness and the selection of engineering treatments at unsignalized crosswalks to improve safety and efficiency of pedestrian crossing.

Finite element modelling of the ionic conductivity of acceptor doped ceria

The ionic conductivity of doped ceria is strongly influenced by temperature, oxygen partial pressure, dopant concentration and microstructure of the material. While theory and experiments generally agree on the influence of the first two parameters, the other influences are still not fully understood. A reliable simulation model of the material’s electrical conductivity is thus necessary to interpret the existing measurements.Until now, prediction of the electrical conductivity of these materials relies mainly on analytical models. This approach yields useful insights but it also has drawbacks. We implement the partial differential equations that govern charge carrier transport and electrical potential in a finite element model. This numerical approach enables us to treat grains of arbitrarily small size and to predict electrical conductivities at any applied current density. The results predicted by our model are compared to the available measurements in literature.