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The challenges of modeling flexible aircraft include appropriate fidelity capturing and validation with experimental data. In fact, the validation of formulations and models for the flexible flight dynamics is indispensable to ensure that all the important phenomena are correctly captured. With this objective, two high-aspect-ratio flexible aircraft have been flight-tested, and coupled aeroelastic–flight dynamics data have been collected to support model validation. Additional ground vibration and static tests were carried out to fully characterize the structural dynamic properties. Numerical models were built based on a linear structural representation but with geometrically nonlinear aerodynamics. Low Reynolds number effects were included in a simplified way with lookup tables of two-dimensional airfoil data. Wing-tip effects were considered via the vortex- and doublet-lattice methods. Propulsive data were obtained with wind-tunnel tests. This paper describes the numerical models, the two aircraft, and their instrumentation and presents the data collected from the aircraft sensors during flight tests. Numerical and experimental results are compared for angular velocities, accelerations, and strains measured at different points of the aircraft. Despite its limitations and simplifications, the numerical model captures the real aircraft main aeroelastic and flight dynamic behaviors.

The use of computational techniques in the design of dry powder inhalers (DPI), as well as in unravelling the complex mechanisms of drug aerosolization, has increased significantly in recent years. Computational fluid dynamics (CFD) is used to study the air flow, inside the DPI, during the patient inspiratory act while discrete element methods (DEM) are used to simulate the dispersion and aerosolization of the drug product powder particles. In this work we discuss the possibility to validate a coupled CFD-DEM model for the NextHaler® DPI device against previously published experimental data. The approximations and assumptions made are deeply discussed. The comparison between computational and experimental results is detailed both for fluid and powder flows. Finally, the potential and possible applications of a calibrated DPI model are discussed as well as the missing elements necessary to achieve a fully quantitative predictive computational model.

This paper proposes a procedure to improve the accuracy of the light aircraft 6 DOF simulation model by implementing model tuning and aerodynamic database correction using flight test data. In this study, the full-scale flight testing of a 2-seater aircraft has been performed in specific longitudinal manoeuver for model enhancement and simulation validation purposes. The baseline simulation model database is constructed using multi-fidelity analysis methods such as wind tunnel (W/T) test, computational fluid dynamic (CFD) and empirical calculation. The enhancement process starts with identifying longitudinal equations of motion for sensitivity analysis, where the effect of crucial parameters is analysed and then adjusted using the model tuning technique. Next, the classical Maximum Likelihood (ML) estimation method is applied to calculate aerodynamic derivatives from flight test data, these parameters are utilised to correct the initial aerodynamic table. A simulation validation process is introduced to evaluate the accuracy of the enhanced 6 DOF simulation model. The presented results demonstrate that the applied enhancement procedure has improved the simulation accuracy in longitudinal motion. The discrepancy between the simulation and flight test response showed significant improvement, which satisfies the regulation tolerance.

This study investigates the compressible-brake-fluid flow characteristics within an electric parking brake (EPB) caliper during the bleeding cycles, subsequently determines the fundamental cause for reduction in brake-bleeding performance, and suggests a new design for its improvements. Three-dimensional simulation validation of the brake-fluid consumption curve is conducted through the parameter study of the air mass flow and bulk modulus. A numerical approach utilizing a three-phase (air, brake-fluid, and brake-fluid vapor) mixture model and a standard k-ω turbulence model is adopted to investigate the flow field details. Based on the unsteady simulation results and experimental verifications for the current and new models of the nut-spindle of a driving part in the EPB caliper, the primary cause for the reduction in the bleeding performance in the EPB caliper is determined to be the trapped air in the thread gap and in the space between the spindle and nut-spindle. Consequently, the head chamfer effect for the nut spindle is beneficial for removing trapped air and leads to performance improvement of 30.3 %.

Although global and regional dynamical models are used to predict the tracks and intensities of hurricanes over the ocean, these models are not currently used to predict the wind field and other impacts over land. This two-part study performs detailed evaluations of the near-surface, overland wind fields produced in simulations of Hurricane Wilma (2005) as it traveled across South Florida. This first part describes the production of two high-resolution simulations using the Weather Research and Forecasting (WRF) Model, using different boundary layer parameterizations available in WRF: the Mellor–Yamada–Janjić (MYJ) scheme and the Yonsei University (YSU) scheme. Initial conditions from the Global Forecasting System are manipulated with a vortex-bogusing technique to modify the initial intensity, size, and location of the cyclone. It is found possible through trial and error to successfully produce simulations using both the YSU and MYJ schemes that closely reproduce the track, intensity, and size of Wilma at landfall. For both schemes the storm size and structure also show good agreement with the wind fields diagnosed by H*WIND and the Tropical Cyclone Surface Wind Analysis. Both over water and over land, the YSU scheme has stronger winds over larger areas than does the MYJ, but the surface winds are more reduced in areas of greater surface roughness, particularly in urban areas. Both schemes produced very similar inflow angles over land and water. The overland wind fields are examined in more detail in the second part of this study.

In the numerical simulation of the macroscopic flow of the concrete, it can optimize the performance indicators of the screw conveyor and improve the uniformity of the material to be discharged in the batch production. The discrete element method is effective. The accuracy of physical parameters of this method is a key issue for the reliability of the simulation results of concrete. In this study, we measured the parameters describing the interaction between gravel, mortar, as well as between these two materials and the wall (steel). The experimentally determined parameters include the particle density, size, shape, coefficient of restitution, coefficients of static, and rolling friction. The cohesion coefficient of mortar particles for batch time was obtained by comparing the spread diameter and flow time in V-funnel experiments and simulation. After these calibration steps, the DEM parameters were validated by comparison of the mass flow rate and driving power by the batch production of screw conveying in simulations and experiments. The calculated results are proved to be close to the experimental data, which demonstrates that the measured DEM parameters are of sufficient accuracy to be used in the simulation of concrete flow performance (mass flow rate, energy consumption) in the screw conveyors.

This paper aims to identify the main cause of the hose whipping phenomenon (HWP) in air refueling, and come up with effective preventive measures. The system-theoretic accident model and process (STAMP), i.e., the system-theoretic process analysis (STPA), was adopted to evaluate the safety of air refueling. Then, the evaluation results were verified with a self-designed simulation validation model. The results show that the HWP is controlled by the docking speed, reel mechanism, and designed hose length; the swing range and tension change of the hose increased under inappropriate speed control; reel control could end the hazardous state of the hose within 50s after docking; the HWP occurred after the hose length was shortened from 22m to 14m. The research findings provide a reference for the prevention of the HWP.

This paper presents a novel design method of the Mission Success Space (MSS) for the evaluation on aircraft contribution effectiveness. MSS concept was proposed for giving success criterion of a mission and judging the success by conventional mission effectiveness with regards to the aircraft capabilities. This space is created by the Mission Success Function (MSF) and the original Effectiveness Index Space (EIS) where empirical equations are usually assumed to be MSFs. Based on this MSS concept, this paper firstly defines the MSS-based evaluation, then further summarizes the evaluation process of the Contribution to System-of-Systems (CSS). More importantly, based on the thought of Inverse Design (ID), a new design method of MSF is presented comprehensively analyzing aircraft’s CSS in a combat mission without using any empirical MSF. The definition of MSS based ID is given and the design procedure is sequentially introduced. Two different confrontation cases are depicted with many details as the simulation validation: Air-to-ground and Penetration. There are two design variables considered for designing MSS in the latter case while only one for the former. However, in both cases, the best design is given by evaluating the Gaussian fitting performance of CSS.

Numerous car-following models have been developed since the 1950s. However, there still exist many traffic phenomena that cannot be demonstrated using the existing models. Therefore, this research proposed a new car-following model, the Asymmetric car-following (ACF) model based on the understanding of driver’s asymmetric behavior, which can explain complex traffic phenomena. We established the asymmetric car-following (ACF) rule under the vehicle’s safety constraints using eight parameters that indicate the driver’s characteristics and vehicle’s performances. To evaluate the ACF model, we performed the simulation for car-following pairs and conducted a comparison analysis with the existing models: Newell, Gipps, GM, and IDM. As a result, the proposed ACF model showed good fitness with the empirical trajectory and the apparent asymmetric behavior compared to others. For further investigation in the congested traffic stream, we simulated a group of vehicles by adding an error term to represent the driver’s unexpected behavior. The simulation showed growth, propagation, and dissipation of the stop-and-go traffic. These results proved that the ACF model has the strength to elaborate on various traffic phenomena, such as traffic hysteresis and stop-and-go traffic.

Addressing the dearth of sustainable tourism teaching simulations, this article details the design, development, testing and validation of a destination development game simulation designed to reinforce the teaching and learning of sustainable tourism principles. We discuss two stages of model development, including an earlier game developed using system dynamics and an evolved version with agent-based modelling extensions, incorporating a flock leadership framework and network theory, which together provided a framework for considering the human dynamics provoked within the simulation interaction. For Study 1, simulation validation was based on feedback received from staff and students of an Australian higher education institution for which students were assessed on their use of the simulation in a classroom setting. The simulation illustrated to the students the complexity of decision-making in tourism destinations, while highlighting the need for a broader range of stakeholder interactions. We detail the initial validation of Study 2 as a precursor to further testing. The development process has highlighted the importance of a coherent and familiar context as background to using such a simulation as a teaching and learning tool. Further validation will be conducted in diverse institutions to trial and observe different modes of uptake of the simulation.

A design technique for modulated surface reactances for 1-D leaky-wave antenna applications based on complete aperture field synthesis is presented. For a given visible-region spectrum corresponding to desired radiation and polarization patterns, the evanescent or invisible-region spectrum is introduced and systematically optimized to render the antenna surface passive and lossless everywhere, while generating the specified far-zone characteristics. Design techniques for linear and circular polarizations excited by a TM-polarized feed surface wave are provided together with design examples with simulation validation. Not based on local periodicity, the proposed technique does not suffer from limitations associated with the traditional sinusoidally modulated reactance surfaces.

Research on automatic lane-change decision is mainly limited to simulation validation and lacks real vehicle validation methods because it is limited by experimental site and automatic driving technology on real vehicles. This paper puts forward a miniature traffic model to simulate the actual traffic scene and achieves to verify the decision control of automatic lane-change scene. The miniature intelligent traffic scene contains miniature vehicles, simplified miniature road traffic environment, and wireless network communication. After testing the basic functions of the miniature traffic scene model, such as automatic lane change, lane keeping, and automatic following, a semi-physical simulation test of the traffic flow composed of the model vehicle and the virtual vehicle is carried out. The semi-physical simulation test includes vehicle-following test of hybrid-condition intelligent driver model, lane-change test of lane-change decision two-vehicle gaming model, and minimizing overall braking induced by lane changes. The results show that the feasibility of the method and of the lane-change decision two-vehicle gaming model of automatic lane change is better in terms of traffic safety, traffic efficiency, and homogeneity. Compared to the minimizing overall braking induced by lane-change model test, the test of lane-change decision two-vehicle gaming model improves 2.26% and 1.5% in the average speed and total driving distance, respectively. The standard deviation of the traffic speed of the lane-change decision two-vehicle gaming model was 28.57% lower than the minimizing overall braking induced by lane changes. Compared to pure simulation verification, the method considers the effects of actual sensor signals and actuator control, which is closer to the actual application.

Ground motion simulation validation is an important and necessary task toward establishing the efficacy of physics-based ground motion simulations for seismic hazard analysis and earthquake engineering applications. This article presents a comprehensive validation of the commonly used Graves and Pitarka hybrid broadband ground motion simulation methodology with a recently developed three-dimensional (3D) Canterbury Velocity Model. This is done through simulation of 148 small magnitude earthquake events in the Canterbury, New Zealand, region in order to supplement prior validation efforts directed at several larger magnitude events. Recent empirical ground motion models are also considered to benchmark the simulation predictive capability, which is examined by partitioning the prediction residuals into the various components of ground motion variability. Biases identified in source, path, and site components suggest that improvements to the predictive capabilities of the simulation methodology can be made by using a longer high-frequency path duration model, reducing empirical V-s30-based low-frequency site amplification, and utilizing site-specific velocity models in the high-frequency simulations. University of Canterbury; QuakeCoRE: The NZ Centre for Earthquake Resilience, National Hazards Research Platform (NHRP); Royal Society of New Zealand's (RSNZ) Marsden Fund; Royal Society of New Zealand's (RSNZ) Rutherford Discovery Fellowship; Royal Society of New Zealand's (RSNZ) Rutherford Postdoctoral Fellowship Published version The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Financial support of this research from the University of Canterbury, QuakeCoRE: The NZ Centre for Earthquake Resilience, National Hazards Research Platform (NHRP), and the Royal Society of New Zealand's (RSNZ) Marsden Fund, Rutherford Discovery Fellowship, and Rutherford Postdoctoral Fellowship are greatly appreciated. High-performance computing resources under the NeSI merit allocation are also greatly appreciated. Public domain – authored by a U.S. government employee

Limited by its low energy capacity, small UAVs have short flight time. Therefore, it is of great significance to improve the endurance performance of small UAVs by applying solar energy technology and dynamic soaring technology which can obtain external energy. This paper analyzes the energy exchange principle of small UAVs using solar energy technology and dynamic soaring technology, and works out the strategy of maximum energy gain. Small UAV flight dynamics model combined with solar power-energy system was built, choosing surround flight path at twilight moment for simulation validation. The advantages of small solar UAV using dynamic soaring technology in energy acquisition in hovering flight and pure dynamic gliding flight are verified, compared with traditional solar vehicle. The significance of combining the two energy acquisition technologies to improve the endurance of small UAV is proved, which provides a basis for further study of all-weather uninterrupted flight in the future.

In order to improve the reliability and real-time of the control system of aero-engine, an intelligent fault-tolerant control system based on the online sequential extreme learning machine (OS-ELM) is proposed against the sensor faults. This system can realize the online fault diagnosis and signal reconstruction without a system model. And while considering the traditional PID control robustness and poor anti-interference ability and other shortcomings, an improved global fast non-singular terminal sliding mode control method is used to obtain better control effects, effectively solve the uncertainty problem in aero-engine, and give full play to aero-engine performance. To verify the feasibility and effectiveness of this system based on the above method, a turbofan engine is taken as the research object and semi-physical simulation experiments on fault-tolerant control are conducted on a semi-physical simulation test platform. Results show that the controller of this system can safely and reliably control the aero-engine without losing its control performance under the circumstance that there are faults in engine sensors. The purpose of fault-tolerant control is reached.

In the cyclic racking evaluation of curtain wall systems, physical testing with instrumentation is the standard method for collecting performance data by most design professionals. The resulting testing of full-scale mockups can provide many types of data, including load and displacement values at different stages of loading through failure. While this type of data is valuable for product/system development/fabrication and design, such data can also provide a means for simulation validation of the curtain wall cyclic performance under simulated earthquake loading. Once the simulation study is validated using the test results, then parametric studies by designers can be conducted with greater ease, ideally with commercial software packages, without the need for testing. For the results of this research study, a practical industry formulated finite element modeling (FEM) approach was used to predict the performance of the curtain wall mockups. Here, unitized four-sided structural sealant glazing (4SSG) curtain wall system mockups that incorporate a re-entrant corner were subjected to cyclic racking displacements per the American Architectural Manufacturers Association (AAMA) 501.6 Structural Sealant protocol. System performances, including displacements, were obtained from the FEM study and used to calculate the effective shear strain of the structural silicone and the drift capacity of the system. This paper describes the details of the techniques developed for FEM, the analysis results, and shows an example application of the numerical modeling approach for mockups with racking test results available. The goal of this modeling approach was to create and test methods that practicing consulting engineers can quickly conduct in their offices on common commercially available software often available to them.

In order to solve the problem of inefficient long-term operation of urban public transport vehicles and the difficulty of finding the cause of the disease, a new analysis idea was designed using machine learning methods. This study aimed to provide a rapid, accurate, and convenient solution model and algorithm to address the drawbacks of traditional analysis tools that are incapable of handling multiple sources of public transport data. Based on a full process analysis of the bus operation status, the influencing factors and calculation methods were defined. Afterwards, the calculation results were used to construct a training set with a Random Forest regression model to obtain the weight ranking of different influencing factors. The results of the simulation validation proved that the model can use the basic data of bus operation to quickly find out the primary factors affecting the operation condition and pinpoint to the bottleneck interval. The method has high accuracy and feasibility. It can be universally applied to the analysis of regular bus scenarios to provide strong decision support for the operation level.

This paper deals with the HEV real-time energy management problem using deep reinforcement learning with connected technologies such as Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I). In the HEV energy management problem, it is important to run the engine efficiently in order to minimize its total energy cost. This research proposes a policy model that takes into account road congestion and aims to learn the optimal system mode selection and power distribution when considering the far future by policy-based reinforcement learning. In the simulation, a traffic environment is generated in a virtual space by IPG CarMaker and a HEV model is prepared in MATLAB/Simulink to calculate the energy cost while driving on the road environment. The simulation validation shows the versatility of the proposed method for the test data, and in addition, it shows that considering road congestion reduces the total cost and improves the learning speed. Furthermore, we compare the proposed method with model predictive control (MPC) under the same conditions and show that the proposed method obtains more global optimal solutions.

Oil shortages and environmental pollution are attracting worldwide attention incrementally. Hybrid falls within one of the effective techniques for those two problems. Taking the loader with high energy consumption and high emission as the target, combined with the hydraulic hybrid technology with high power density and strong energy storage capacity, the parallel hydraulic hybrid loader (PHHL) based on brake energy regeneration is proposed. Firstly, the dynamic models of the key components of the PHHL are established, and the parameters of the part which coincides with the ordinary loader are corrected based on the V-type duty cycle. Then, consid-ering the energy recovery efficiency as well as the characteristics of the loader from the V-type duty cycle, the parameters for several major parts of the energy regeneration system (ERS) were calculated and matched. Then, based on the initial matching, the improved adaptive genetic al-gorithm (AGA) is employed to optimize the control variable of the control strategy and the design parameters of ERS to enhance the economic benefit and performance of the ERS. Furthermore, a simulation validation was conducted. Simulation results show that the ERS with optimized pa-rameters could improve the fuel-saving effect by 25% compared to the ERS with initial parameters, which indicated the rationality of the optimized parameters. Finally, the fuel consumption test of the PHHL prototype under the V-type duty cycle is performed. The results show that the PHHL with the optimization scheme can achieve 9.12% fuel saving, which is on the brink of the potential of brake energy recovery and verifies the feasibility of applying hydraulic hybrid technology on the loader.

Proper validation of a simulation model is essential for confidence in its accuracy and credibility. However, many of the most effective approaches for simulation validation require access to data that may be unavailable. Metamorphic Testing (MT), an approach from traditional software testing, has been shown to be useful for verification of simulation software in similar situations. Recent research shows that MT can be applied to the validation of agent based and discrete event simulation models as well. In this paper we build on that work and show how MT can be applied to hybrid simulation models. We demonstrate the effectiveness of our approach by applying it on a case study of helping behavior among servers in a restaurant.

Properties represent the state of a system at any instance of time or for a period of time. We consider properties as a common concept for Experimental Frame (EF) that can be used for simulation and modeling checking. This affords to define experimental frames that can evaluate the dynamics of models of systems purposed for both validation and verification. We show this approach through simulation of Parallel DEVS models as well as model checking of Constrained-DEVS models. We develop experiments for simulating and model checking a prototypical Network-on-Chip (NoC) system. The models and experiments are developed and executed using the DEVS-Suite tool. New capabilities of this tool include support for defining experimental frames that stimulate and monitor executions of models. The proposed approach with the developed execution engine affords both simulation validation and model checking verification.

A newly designed passive loop thermosyphon cooling system (whose design and simulation are described in a companion ITHERM2021 paper) was prototyped and tested at different levels of CPU heat load, air temperature and volumetric flow for two environmentally friendly working fluids: R1233zd(E) and R1234ze(E). The light and compact all aluminum cooling unit (patent-pending [1]) has a total height of 66mm and it is dimensioned to allow two units to fit side-by-side on two CPUs in 2U datacenter servers. The prototype was bench tested to operate safely for R1233zd(E) at heat loads from 100W up to a very high heat load of 700W, air inlet temperatures from 25°C to 30°C and air flow rates from 40CFM to 178CFM, yielding measured junction temperatures from 35°C and 90°C and thermal resistance as low as 0.085 °C /W. For R1234ze(E), the tests covered heat loads from 50W to 500W, air inlet temperatures from 26°C to 30°C and air flow rates from 40CFM to 118CFM with observed junction temperatures between 32°C and 92°C and thermal resistance as low as 0.081 °C /W. The pseudo-CPU footprint area was 16cm2, corresponding to heat fluxes from 3.125W/cm2 to 43.75W/cm2. Cold start-up tests were performed and are discussed. Finally, a validation of JJ Cooling Innovation’s inhouse simulator used for the thermal-fluidic design of the unit is presented, showing the capability of the inhouse solver to predict the performance of this LTS cooling system with a high level of confidence (with mean error of 2.1°C and maximum error of 5.8°C in junction temperature).

Metamorphic testing has been shown to be useful in testing "non-testable" programs in many domains. Modeling & simulation is one such domain, where both verification and validation can be difficult due to lack of oracles. Although the definition of verification and validation vary slightly in modeling and simulation when compared to standard software, we show that metamorphic testing is appropriate in both aspects of ensuring that a simulation model is accurate. In this paper we expand on our five years of prior work on metamorphic testing for simulation validation to show how metamorphic testing can be used for verification as well, and how the previously defined guidelines for validation can be utilized in eliciting metamorphic relations for verification.

The aim of this work is to improve numerical predictions of natural convection heat transfer inside of gas turbines. It is desirable for engineers to use numerical simulations be able to accurately predict the heat transfer inside of a gas turbine casing during engine shutdown. This will help them to understand and alleviate problems such as engine casing distortion. A natural convection test rig was constructed to provide simulation validation data. The rig represented a section of a large gas turbine casing and operated at the same Rayleigh number as a real engine. The casing rig was able to provide a unique dataset that could not be obtained through real engine measurements. Analysis of the casing rig was performed using a large eddy simulation and RANS simulations. It was found that the baseline RANS simulation did not predict the heat transfer accurately enough for engineering use. The simple gradient diffusion hypothesis (SGDH) turbulent heat flux model used in the baseline simulations was replaced by more advanced generalised gradient diffusion hypothesis (GGDH). A modification to the GGDH model, called GGDH+, was developed to account for buoyancy effects on the turbulent heat flux. The GGDH+ model was then able to give heat transfer predictions comparable to the LES results.

This paper presents on-going challenges in the present paradigm shift of earthquake-induced ground motion prediction from empirical to physics-based simulation methods. The 2010–2011 Canterbury and 2016 Kaikoura, New Zealand earthquakes are used to illustrate the predictive potential of the different methods. On-going efforts in simulation validation and theoretical developments are then presented, as well as the demands associated with the need for explicit consideration of modelling uncertainties. Finally, discussion is also given to the tools and databases needed for the efficient utilisation of simulated ground motions both in specific engineering projects as well as for near-real-time impact assessment.

This paper is devoted to design of a non-linear model predictive controller (NMPC), which will swing-up and stabilize an inverse rotary pendulum known as the Furuta Pendulum. This paper presents a simulation validation of the NMPC strategy using a full-fidelity non-linear mathematical model of the Furuta pendulum obtained from the Euler-Lagrange motion equations. The NMPC strategy was implemented in MATLAB using the MATMPC toolbox.

Purpose The purpose of this paper is to verify the correctness and feasibility of simultaneous localization and mapping (SLAM) algorithm based on red-green-blue depth (RGB-D) camera in high precision navigation and localization of celestial exploration rover. Design/methodology/approach First, a positioning algorithm based on depth camera is proposed. Second, the realization method is described from the five aspects of feature detection method, feature point matching, point cloud mapping, motion estimation and high precision optimization. Feature detection: taking the precision, real-time and motion basics as the comprehensive consideration, the ORB (oriented FAST and rotated BRIEF) features extraction method is adopted; feature point matching: solves the similarity measure of the feature descriptor vector and how to remove the mismatch point; point cloud mapping: the two-dimensional information on RGB and the depth information on D corresponding; motion estimation: the iterative closest point algorithm is used to solve point set registration; and high precision optimization: optimized by using the graph optimization method. Findings The proposed high-precision SLAM algorithm is very effective for solving high precision navigation and positioning of celestial exploration rover. Research limitations/implications In this paper, the simulation validation is based on an open source data set for testing; the physical verification is based on the existing unmanned vehicle platform to simulate the celestial exploration rover. Practical implications This paper presents a RGB-D camera-based navigation algorithm, which can be obtained by simulation experiment and physical verification. The real-time and accuracy of the algorithm are well behaved and have strong applicability, which can support the tests and experiments on hardware platform and have a better environmental adaptability. Originality/value The proposed SLAM algorithm can deal with the high precision navigation and positioning of celestial exploration rover effectively. Taking into account the current wide application prospect of computer vision, the method in this paper can provide a study foundation for the deep space probe.

Simulation validation, demonstrating that a simulation accurately represents the system it studies, poses a particularly potent form of the oracle problem. A simulation must be validated for its results to be reliable, but often no oracle exists due to the nature of simulations. We propose taking the metamorphic testing (MT) approach from the realm of software verification and applying it for validating executable simulation models. By establishing pseudo-oracles based on metamorphic relations between parameters and behaviors within an executable model, we can create a methodical approach for validating simulation models. We propose an overall framework and guidelines to apply MT for simulation validation, with details for two prevalent simulation approaches: agent-based simulation models (ABM), and discrete-event simulation (DES) modeling. Through three case studies, we demonstrate the successful application of MT toward validating three different simulation models: an ABM of gossip propagation, an ABM of cancer, and a DES of airport check-in and security.

In this paper, a distributed filtering scheme is presented to deal with the fault detection problem of nonlinear stochastic systems with wireless sensor networks (WSNs). The nonlinear stochastic systems, which are of discrete-time form, are represented by interval type-2 (IT2) Takagi–Sugeno (T–S) fuzzy models. Each sensor of the WSN can receive measurements from itself and its neighboring sensors subject to a deterministic interconnection topology. Independent random variables obeying the Bernoulli distribution are formulated to characterize the randomly occurred packet losses between the WSN and the filter unit. To generate residual signals for evaluation functions of the fault detection mechanism, a novel type of IT2 T–S fuzzy distributed fault detection filter is proposed corresponding to each sensor node. Additionally, a fault reference model is adopted for improving the performance of the fault detection system. A new overall fault detection system is formulated in an IT2 T–S fuzzy model framework. Applying Lyapunov functional approach, we concentrate on the analysis of stability and performance of the resulting fault detection system. New techniques are utilized to handle the decoupling problem in design procedure. The desired parametric matrices of the fuzzy filters are designed subject to a developed criterion, which is a sufficient condition of the robust mean-square asymptotic stability for the overall fault detection system with a disturbance attenuation performance. Finally, a truck-trailer system with a four-node WSN is established for simulation validation. In simulations, the mincx function of the MatLab 2017a in Windows 10 OS is used to optimize the level of the disturbance attenuation performance, and to obtain the filter gains for the established system. By comparing the different time instants when the residual evaluation functions exceed their respective thresholds, simulation results successfully validate the effectiveness and applicability of the presented distributed fault detection scheme.

This article presents the simulation, validation and implementation of a temperature sensor based on RO (Ring Oscillator) in order to carry out a thermal study for the detection and localization of thermal peaks in an integrated circuit (CI). The input temperature, angles, distance as well as certain frequencies will be obtained using the GDS (gradient Direction Sensor) method based on RO. In this work, a simulation with the ModelSIM tool as well as the technological validation of the degree of integration with the NCLAUNCH Cadence tool and check this type of fully digital temperature sensor includes a number of exact inverters that can be logically inserted. In addition, a DE1 FPGA cyclone of the V 5CSEMA5F31C6 family is used for implementation. Before the transition to FPGA board implementation and verification, the use of the VHDL code and its bench test is required to describe three inverters that form a ring oscillator, in order to validate the results obtained after the synthesis Quartus Prime. This document provides a solution to thermal constraints and local overheating in the design of complex systems, which has been a major concern for designing integrated circuits.

Model-based development is increasingly used in embedded systems, which are often deployed in a safety-critical environment. Verification techniques, supporting the development process can not only increase safety, but also help to speed up the process. In many cases models are designed with block diagrams, assisting rapid prototyping. However, automated verification is, thereafter, often applied to the resulting code. Instead of focusing on code, we apply verification techniques to models consisting of block diagrams and MATLAB code. We propose to combine a value and slope range analysis, with symbolic methods. In this way, our concept can not only prove properties in models, but also check rate requirements automatically, which arise from physical constraints of the environment. We evaluate our work in case studies from ongoing research projects. These case studies cover the domains of clinical intensive care, autonomous drone control and driver assistance. All systems are also evaluated with a commercial verification tool, highlighting benefits of the tool and our implementation.

This book provides a broad and comprehensive look at hybrid powertrain technologies for commercial vehicles. It begins with the fundamentals of hybrid powertrain systems, government regulations, and driving cycles, then provides design guidelines and key components of hybrid powertrains for commercial vehicles. It was written for vehicle and component engineers and developers, researchers, students, policymakers, and business executives in the commercial vehicle and transportation industries to help them understand the fundamentals of hybrid powertrain technologies and market requirements for commercial vehicles. It is useful for anyone who designs or is interested in hybrid powertrains and their key components. The term ‘commercial vehicle’ applies to everything from light delivery vehicles to class 8 long haul trucks, buses, and coaches. These vehicles are used for a wide range of duties, including transporting goods or people and infrastructure service.

This work illustrates the analysis of Film Bulk Acoustic Resonators (FBAR) using 3D Finite Element (FEM) simulations with the software OnScale in order to predict and improve resonator performance and quality before manufacturing. This kind of analysis minimizes manufacturing cycles by reducing design time with 3D simulations running on High-Performance Computing (HPC) cloud services. It also enables the identification of manufacturing effects on device performance. The simulation results are compared and validated with a manufactured FBAR device, previously reported, to further highlight the usefulness and advantages of the 3D simulations-based design process. In the 3D simulation results, some analysis challenges, like boundary condition definitions, mesh tuning, loss source tracing, and device quality estimations, were studied. Hence, it is possible to highlight that modern FEM solvers, like OnScale enable unprecedented FBAR analysis and design optimization.

Ring size distribution of silicate glass can be determined from the first sharp diffraction peak of neutron structure factor., Silicate glasses have no long-range order and exhibit a short-range order that is often fairly similar to that of their crystalline counterparts. Hence, the out-of-equilibrium nature of glasses is largely encoded in their medium-range order. However, the ring size distribution—the key feature of silicate glasses’ medium-range structure—remains invisible to conventional experiments and, hence, is largely unknown. Here, by combining neutron diffraction experiments and force-enhanced atomic refinement simulations for two archetypical silicate glasses, we show that rings of different sizes exhibit a distinct contribution to the first sharp diffraction peak in the structure factor. On the basis of these results, we demonstrate that the ring size distribution of silicate glasses can be determined solely from neutron diffraction patterns, by analyzing the shape of the first sharp diffraction peak. This method makes it possible to uncover the nature of silicate glasses’ medium-range order.

International audience; A simulation can be a complex architecture of simulation models, simulation tools, and computing hardware. However, its development often relies on informal procedures and can begin without a clear, complete, and formal definition of the simulation needs. Simulation traceability is then compromised, which prevents from easily validating whether a simulation meets the needs, or understanding the purpose of a simulation model that can be reused. This paper proposes an approach to improve the definition of simulation needs using Model-Based Systems Engineering. Based on the semi-automatic processing of a system architecture, it presents a new method to formulate a so-called “simulation request” which covers (1) the part of the system to be simulated; (2) the objective of the simulation; (3) the simulation quality, cost, and delivery; (4) the test scenarios; (5) the data for simulation calibration and validation; and (6) the verification and validation of the simulation. All the tooling required for the formulation of the simulation request were prototyped in a SysML editor, with machine learning capabilities for the choice of test scenarios. The method and tooling were tested for the case of an autonomous car passing under traffic lights.

In this paper, a methodology is discussed concerning the measurement of yarn’s angle of two different glass-reinforced polypropylene matrix materials, widely used in the production of automotive components. The measurement method is based on a vision system and image processing techniques for edge detection. Measurements of angles enable, if accurate, both useful suggestions for process optimization to be made, and the reliable validation of the simulation results of the thermoplastic process. Therefore, uncertainty evaluation of angle measurement is a mandatory pre-requisite. If the image acquisition and processing is considered, many aspects influence the whole accuracy of the method, the most important have been identified and their effects evaluated with reference to two different materials, which present different optical-type characteristics. The influence of piece geometry has also been taken into account, carrying out measurements on flat sheets and on a semi-spherical object, which is a reference standard shape, to verify the effect of thermoforming and to tune the process parameters. Complete uncertainty in the order of a few degrees has been obtained, which is satisfactory for purposes of simulation validation and consequent process optimization. The uncertainty budget also allowed individuation of the most relevant causes of uncertainty for measurement process improvement.

In this paper we propose a novel closed-loop model-less feedback control scheme for soft manipulators with Jacobian matrix adaptation. As the major merit, this approach does not rely on a specific kinematic model and thus has wide applicability and portability for different kinds of soft manipulators. We make use of closed-loop control, convex optimization and adaptation strategy to estimate the Jacobian matrix for trajectory tracking tasks. In the simulation validation, we adapt the algorithm to a two-section soft manipulator of piece-wise constant curvature to track a desired trajectory. Furthermore, we compare our algorithm with two other model-less algorithms and a model-based algorithm with noise on their tracking performances. Validation results prove the feasibility of this simple yet effective model-less feedback control scheme.

In our research, we address the problem of coordination and planning in heterogeneous multi-robot systems for missions that consists of a set of spatially localized tasks. Conventionally, this problem has been framed as a task allocation problem that maps tasks to robots. However, all previous work assume that tasks are atomic procedures. In this work we relax this assumption and adopt a non-atomic model of tasks that enables robot accomplishing mission tasks in an incremental manner over disjoint periods of time, precisely to account for the possibility of having a task being serviced by multiple individual contributions over time. This model can be useful in search and rescue scenarios: the same portion of the environment can be explored at different times by different agents using different sensors. We propose a cooperative, load-balancing task allocation and scheduling algorithm based on sequential single-item auctions (CoLoSSI). Our approach explicitly considers the non-atomicity of tasks and promotes synergies between agents enabling cooperation while at the same time maintaining computational tractability. We also study a fully distributed implementation of the task allocation approach in sparse, communication-restricted scenarios, and propose an effective strategy to enhance its computational efficiency. A computational and simulation validation is also carried out, confirming the efficacy of the proposed approach for generating good quality mission plans with low computational effort.

To ensure the safety running of power grid, the on-line monitoring of power equipment is essential to the power grid, compared with the traditional periodic maintenance. The existing on-line monitoring methods have some limitations. In this paper, a novel method combined low-frequency dielectric loss method with signal injection into power grid method is proposed. For this method, a low frequency signal is injected into the power grid from the open triangle side of the PT. Then the dielectric loss factor can be achieved to know the insulation situation of the cable. To validate the effectiveness of the novel method, simulation tests are done. For the simulation validation, a model is established in COMSOL software and a thermal aging cable and a water tree aging cable are both simulated. All the simulation results indicate that the insulation situation of power cable can be studied through the novel method effectively.

Rockfalls are one of the most common natural hazards in mountainous areas that pose high risk to people and their activities. Rockfall risk assessment is commonly performed with the use of models that can simulate the potential rockfall source, propagation and runout areas. The quality of the models can be improved by collecting data on past rockfall events. Mobile crowdsourcing is becoming a common approach for collecting field data by using smartphones, the main advantages of which are the use of a harmonised protocol, and the possibility of creating large datasets due to the simultaneous use by multiple users. This paper presents a new methodology for collecting past rockfall events with a mobile application, where the locations and attributes of rockfall source areas and rockfall deposits are collected, and the data are stored in an online database which can be accessed via the WebGIS platform. The methodology also presents an approach for calculating an actual source location based on viewshed analysis which greatly reduces the problem of field mapping of inaccessible source areas. Additionally, we present a rockfall database in the Alpine Space that has been created by the presented methodology, and an application of collected data for the calibration and validation of two rockfall models (CONEFALL and Rockyfor3D).

The geometric model and performance criteria of a stereo camera sensor are proposed for the purpose of sensor performance optimization. In particular, the details of the geometric model is presented to characterize the configuration parameters of the stereo camera sensor. Six effective criteria are then synthesized to measure the sensor performance based on the geometric model, including depth resolution, permissible degree of orientation, visual resolution, field of view, focus, and occlusion. A sample optimization task is presented to show the effectiveness of the model and the performance criteria with the simulation validation using the gradient-ascent based algorithm and the improved genetic algorithm respectively.

The paradigm of smart grids has been continuously addressing new challenges in terms of power electronics converters, for instance, to deal with technologies like renewables, electric mobility, energy storage, and hybrid power grids. Allied with this context, a novel topology of modular multilevel bidirectional (MMB) non-isolated dc-dc converter is proposed in this paper. Taking into consideration the nature of the proposed MMB dc-dc converter, it is appropriated to operate as back-end converter linked to front-end ac-dc converters based on cascade structures, i.e., with more than one dc-link. As unique features, the proposed MMB dc-dc converter can operate with five-voltage levels, allowing to reduce the voltage stress in each semiconductor, and it is controlled based on the interleaved principle of operation, although it is not an interleaved converter. A dedicated pulse-width modulation, as well as voltage and current control strategies, are proposed and clearly explained along the paper. The claimed distinctive features of the proposed MMB dc-dc converter are supported by analytic description and by computer simulation validation, considering steady-state and transient-state operations in relevant conditions of the dc interfaces.

The air supply system control strategy is a significant challenge issue of PEM(Polymer Electrolyte Membrane) fuel cells. In this paper, an observer-based model predictive control scheme is proposed for oxygen excess ratio control to avoid the oxygen starvation without using physical sensor of oxygen excess ratio based on a nonlinear dynamic model. Firstly, a sliding mode PI observer is proposed to estimate the cathode pressure and oxygen excess ratio, and the convergence is also discussed by a constructed Lyapunov function. Then, the observer-based model predictive controller is designed for the oxygen excess ratio control. Finally, the simulation validation is demonstrated to validate the effectiveness of the proposed observer and the control scheme by a high fidelity model.

Load frequency regulation is one of the most vital and complex ancillary services in a deregulated power system. Increasing penetration from renewable energy sources in an integrated power system (IPS) further escalates the related control complexity due to a considerable decrement in IPS’s effective inertia. This may incur additional costs and can even lead to the destabilization of IPS. To overcome these problems in frequency regulation, this work proposes and investigates the use of an intelligent, direct adaptive control scheme, i.e., self-tuning fractional order fuzzy PID (STFOFPID) controller with and without the presence of a recently devised energy storage unit, i.e., the redox flow battery. The IPS’ efficacy with the STFOFPID controller is validated for various contracts in a deregulated operation mode for considered three area IPS. Extensive simulation studies are carried out, and detailed comparative studies have been drawn with conventional PID and fractional order PID controllers for load frequency regulation in Poolco, bilateral, and contract-violation mode of operation. Robustness analysis in terms of parametric variations in different nonlinearities present in a reheated thermal power plant is also carried out, and the efficacy of the STFOFPID controller is established using a thorough quantitative comparative analysis. The real-time digital simulation validation of the investigated control structure has been carried out on OPAL-RT 4150 based on Xilinx Kintex-7 FPGA board with INTEL multi-core processor.

The DC bias of AC transformer will be caused by grounding electrode which pour DC into the ground, DC bias is affected by the ground condition near the ground electrode, the parameters of power equipment and lines, and the operation mode of power grid, among which the geodetic parameters near the ground electrode are uncertain factors. In this paper, a method of estimating geodetic parameters is proposed. The probability statistics of moments of random variables are obtained according to the probability distribution of random factors or random disturbances. The uncertain parameters are estimated such as earth resistivity and equivalent area, and the error analysis of uncertain factors is completed. The simulation validation of the estimation method is carried out, and the variation of the ground potential with uncertainties is given, which provides data support for the calculation of DC bias in the expansion of DC project.

Optimization algorithms have been successfully applied to the automatic design of analog integrated circuits. However, many of the existing solutions rely on expensive circuit simulations or use fully customized surrogate models for each particular circuit and technology. Therefore, the development of an easily adaptable low-cost and efficient tool that guarantees resiliency to variations of the resulting design, remains an open research area. In this work, we propose a computationally low-cost surrogate model for multi-objective optimization-based automated analog integrated circuit (IC) design. The surrogate has three main components: a set of Gaussian process regression models of the technology&rsquo, s parameters, a physics-based model of the MOSFET device, and a set of equations of the performance metrics of the circuit under design. The surrogate model is inserted into two different state-of-the-art optimization algorithms to prove its flexibility. The efficacy of our surrogate is demonstrated through simulation validation across process corners in three different CMOS technologies, using three representative circuit building-blocks that are commonly encountered in mainstream analog/RF ICs. The proposed surrogate is 69 X to 470 X faster at evaluation compared with circuit simulations.

Indoor Terahertz Synthetic Aperture Radar (SAR) is an emerging technology for material characterization, high resolution imaging and localization. In comparison to optical technology, it provides benefits in hazardous scenarios such as fire in a building as objects inside the building can be characterized and localized. The principles of SAR are well established but the main challenge lies with extending this technology to high frequencies and indoor environment. To investigate this technology, imaging geometry and system parameters have to be evaluated respectively. This paper explains the signal processing of SAR and presents the imaging geometry for an indoor scenario. Further, it evaluates the parameters for high resolution imaging and localization. Based on these parameters, system design has been simulated and results of 2D high resolution indoor SAR imaging at 300 GHz are presented. Additionally, the proof of theoretical resolution across the range and azimuth is shown with the simulation results.