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The National Aeronautics and Space Administration (NASA) is currently developing the next generation of spacesuits for use in future exploration missions. This effort, referred to as the Exploration Extravehicular Mobility Unit (xEMU), has been underway since 2015 with the goal of demonstrating the new technologies during a mission to the International Space Station (ISS). Due to the complexity of the xEMU system, and particularly its portable life support system (PLSS), computer simulations are heavily relied on in the development process, from dynamic loads analysis to software verification. The models of the physical systems that are currently being used for system-level simulations are mostly empirical, where the underlying formulas are mathematical fits to test or simulation data. An advantage of this approach is the fact that these models are very performant and can be used in real-time applications such as user interface testing and operator training. The research presented in this paper describes a different approach to modeling and simulation. A simulation tool focused on life support systems for human spaceflight in general and PLSSs in particular has been under development at the Technical University of Munich (TUM) since 2006. The spacesuit specific variant of this tool is called The Virtual Spacesuit (V-SUIT) and is now being utilized in the current spacesuit development process at the NASA Johnson Space Center (JSC). In contrast to the previously mentioned empirical models, V-SUIT uses a first-principles-based, bottom up modeling approach, where basic physical, chemical or biological effects are modeled at the lowest level and the component and system models are created using these fundamental building blocks. This enables the simulation to account for effects, and especially off-nominal situations, that may not be within the range of validity of the empirical models. This paper presents the structure of and the rationale behind V-SUIT itself as well as a status report on the ongoing effort to integrate it with the existing simulation systems in use at JSC, which is based on Trick/GUNNS. As a proof of concept, a single component model from V-SUIT, that of the spacesuit water membrane evaporator (SWME), has been integrated with NASA's simulation tool. Results include comparisons of the performance of the two simulation systems and a description of challenges that were encountered during implementation. The paper closes with an outlook towards the future developments that are planned for V-SUIT within the xEMU development program. • A novel approach to dynamic system-level simulations is applied to a spacesuit. • Multi-disciplinary, bottom-up modeling instead of domain-specific, top-down models. • Performance shown to be fast enough to provide value during system development. [ABSTRACT FROM AUTHOR]

Assembly accuracy analysis plays a very important role in verifying whether the design scheme of geometric accuracy in the product design stage can meet the functional requirements of mechanical product. Form deviations, position and orientation deviation are inevitable in manufactured parts, and must be considered during assembly accuracy analysis. With regard to the representation of form deviations, it is verified that skin model shapes are effective. However, the existing simulation approaches of skin model shapes for cylindrical parts are mainly based on gaussian random field, without considering the spatial distribution characteristics of form deviations in dealing with the relationship between geometrical and dimensional deviation for cylindrical parts. Especially, when considering local surface deformations of cylindrical mating surfaces generated during the assembly process, the form deviations with different distribution characteristics leads to different contact deformation, which may have further influence on assembly accuracy analysis of cylindrical parts. To address above problems, this paper proposes a simulation method of skin model shapes of cylindrical parts based on Non-Gaussian random field considering the spatial distribution characteristics of form deviations, and the local surface deformations are analyzed with a boundary element method. Based on above, the relative positioning deviation of cylindrical mating surfaces is obtained considering the influence of form deviations and local surface deformations. Finally, the effectiveness of the proposed method is verified with case studies. Specifically, the results of case study reveal that the influences of form deviations considering spatial distribution characteristics and local surface deformations cannot be ignored for assembly accuracy analysis of cylindrical parts. In addition, for the relative positioning deviation of cylindrical mating surfaces for loose fit, the influence of local surface deformations on translational deviations along the x-axis and y-axis is greater than that on rotational deviations around the x-axis and y-axis. • A skin modeling method of cylindrical parts is proposed based on Non-Gaussian random field. • Spatial distribution characteristics of form deviations and local surface deformations are considered. • CG-DC-FFT method is adopted to solve local surface deformations of cylindrical mating surfaces. • Form deviations of cylindrical mating surfaces have influence on assembly accuracy analysis. • Local surface deformations of cylindrical mating surfaces have influence on assembly accuracy analysis. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) systems have become an integral and widespread part of renewable energy generation. In combination with energy storage, they offer a variety of advantages such as increased self-sufficiency or improved grid stability. However, geographic location, subsidies, energy tariffs, size of PV panels and battery, and other factors significantly influence the overall performance and profitability of the system. Solving this complex task of system design and component dimensioning is not easy. The diversity and multitude of parameters therefore usually requires the help of, more or less complex, computer simulations. This led and still leads to a high publication activity on techno-economic and other optimizations for such systems. However, the operating strategies and component models are often oversimplified, leading to results with significant errors. The goal of this paper is to provide in-depth insight into component modeling and parametrization for PV module, battery energy storage, and inverter, as well as giving suggestions on appropriate control strategies. The focus lies on the description of suitable simple-but-accurate models and their parametrization. In order to avoid the effort of having to conduct measurements for component characterization, an approach relying on values presented in product data sheets is considered. Furthermore, the effects of model simplifications, as they are found in many publications, are shown. Finally, the importance of an uncertainty analysis for the entire simulation is discussed in order to gain insight into the accuracy of the calculated simulation results and their dependency on model- and input-parameters. • Photovoltaic system modeling/simulation. • Component modeling for PV module, battery energy storage and inverter. • Suitable simple-but-accurate models and their parametrization • Characterization relying on product data sheets with minimal informations. [ABSTRACT FROM AUTHOR]

• A new reliability method combining relevance vector machine and subset simulation importance sampling is proposed. • The ability of surrogate model-based subset simulation importance sampling to handle multiple failure mode problems is achieved. • An efficient update strategy is employed to improve the prediction accuracy of relevance vector machine and avoid unnecessary iterations. • The proposed method improves computational efficiency while ensuring the accuracy of the result. Evaluating the failure probability of engineering structures involving implicit performance functions generally requires time-consuming finite element simulations. The computational effort is usually unbearable, especially for small failure probability. This paper proposes a new reliability analysis method combining relevance vector machine and subset simulation importance sampling, which guarantees the accuracy of results and improves the computational efficiency. In this method, relevance vector machine is first applied to approximate relatively coarse limit states. Then, subset simulation importance sampling is executed based on the constructed relevance vector machine. To improve the prediction accuracy, samples from first and last level are used to refine relevance vector machine. Since only the samples of last level are involved in the calculation of the failure probability, and the updated relevance vector machine has a very high prediction accuracy for the samples of last level, the obtained failure probability is extremely accurate. In addition, the samples are predicted by the well-constructed relevance vector machine rather than evaluated with real performance functions, which drastically decreases the calculation time. To reduce redundant iterations in the update process, a novel learning function based on the current design of experiment position and a stopping condition based on error estimation of reliability prediction are employed. Furthermore, the K-means clustering algorithm is utilized to implement the ability of surrogate model-based subset simulation importance sampling to handle multiple failure mode problems. The efficiency and accuracy of the proposed method are verified by four examples involving different types of features. [ABSTRACT FROM AUTHOR]

A composite contact algorithm for a complex particle system containing polyhedrons and super-ellipsoids is proposed in this paper to simulate the grinding process of ore in a ball mill. In this algorithm, the contacts between polyhedrons are calculated based on the overlapping volume method, and the contacts between super-ellipsoids are determined by a deepest point method. The contacts between super-ellipsoids and polyhedrons are obtained by transforming super-ellipsoids into polyhedrons, and then using the overlapping volume method between the polyhedrons. The increase in the number of faces of the super-ellipsoid contributes to the closer shape to the real shape. In this paper, experimental researches and numerical simulations are carried out to validate the accuracy of this composite contact algorithm. Furthermore, the influence of the ratio of super-ellipsoids and polyhedrons, the number of faces of converted super-ellipsoid, and the sharpness of the super-ellipsoid on the computational efficiency are compared in both box filling process and particles mixing process in a rotating tumbler. Finally, the stability and feasibility of this composite contact algorithm is tested in a ball mill application containing more particles. Unlabelled Image • A contact algorithm for polyhedron-super-ellipsoid particle system is proposed. • Experiments and numerical simulations are carried to validate this algorithm. • The computational efficiency of this composite contact algorithm is studied. • The stability and feasibility of this algorithm is tested in a ball mill application. [ABSTRACT FROM AUTHOR]

Economic nonlinear model predictive control (ENMPC) is a strong candidate for controlling wind turbines (WTs). In the model predictive control (MPC) group, the model is the crucial component for the true controller performance. It is common to use simplified models to reduce the problem complexity. These models neglect some of the underlying dynamic responses of real wind turbines. This paper simulates the case in which high accuracy nonlinear models describe both the plant and the controller. The results will be compared to reduced-order models in order to extract conclusions and decide the most appropriate model for WT control. On the other hand, one of the main features of MPC and ENMPC is the concept of receding prediction horizon, which considers the future evolution of the plant to compute the control action. The error of prediction will drastically reduce MPC performance. Also, rapid variation in wind speed can cause problems since wind turbines cannot easily follow these sudden variations due to their high inertia and aerodynamic characteristics. This paper provides an advanced control approach to improve the energy extraction from turbulent wind and enhance wind turbine durability. By implementing this method, the wind speed forecasting is done with a combination of artificial neural networks (ANN) and dynamic equations applied in ENMPC. The results show a significant enhancement of the control performance. • Enhancing the net energy of variable speed wind turbines (WTs). • Considering high accuracy nonlinear models for wind turbine simulation. • Comparing reduced-order models to choose the most appropriate model for WT control. • Suggesting an advanced control approach combining wind speed forecasting with ENMPC. • Improving ENMPC performance, and thereby increasing the power output of WT. [ABSTRACT FROM AUTHOR]

A Physical Internet of hubs ('PI-hubs') is a network of logistics terminals that allow shipments to flow through, similar to the flow of Internet data packets. PI-hub networks are a recent proposal and their properties have not been studied in detail. In this paper we model PI-hub networks using the theory of queuing networks, particularly, Jackson queuing networks. Under certain assumptions, PI-hub networks behave like Jackson queuing networks, and thus analytical methods can be used to calculate important properties such as throughputs, processing times, traffic size etc. In this paper we analyse the performance characteristics (throughput, queue size) for each PI-hub and for the whole PI-hub network. [ABSTRACT FROM AUTHOR]

• A multi-field coupling model and simulation platform are based on COMSOL5.3. • The effects of process parameters and reactor structure on coating silicon nitride film are studied concurrently. • Transforming dynamic coating problems into static problems for simulation research. This paper builds a physical model by using the finite element method on COMSOL simulation platform to simulate the in-line PECVD process. The in-line PECVD simulation model couples the flow field, thermal field, chemical reaction field and plasma field and is verified through experiments. In addition, a new simulation strategy is proposed to solve the problem of dynamic coating silicon nitride film. Through this simulation method, process parameters and structural parameters of the in-line PECVD equipment are optimized. Effects of microwave tube position, microwave shield size, total gas flow, pressure and temperature on main coating reaction region is studied. The results have shown that the position of microwave tube, the total gas flow and temperature have greater influence on the region of reaction zone, the concentration distribution of reactants and the thickness of SiN x H y film. Through optimizing process parameters and structural parameters, the coating rate of SiN x H y film can be increased from 0.0607 nm/s to 0.15 nm/s and the deposition thickness can be increased from 6.78 nm to 15.59 nm. The molar concentration of SiN x H y particles in the reaction region has grown by more than 23.5%. And the relative intensity of reaction field inside PECVD chamber has increased by 1.3–2.3, which is calculated by molar concentration ratio of SiN x H y particles. This paper provides a reference for the optimization of in-line PECVD equipment. [ABSTRACT FROM AUTHOR]

A novel LMR-based optical fiber sensor fabricated with SnO 2 thin film is proposed in this paper, and SnO 2 nanoparticles overlayed on film are further utilized to raise the sensitivity of sensor. The numerical SnO 2 sensing models coated with SnO 2 NPs of two different particle interval are constructed, and the sensitivity enhance by 24.5% and 55.1% respectively compare to that only with SnO 2 film. In the following research experiments, layer-by-layer method is firstly applied in deposition of SnO 2 film and the enhancement in sensitivity caused by SnO 2 NPs tallies with the theoretical predictions. Finally, this paper goes further into the principles of sensitizing combined with the simulation of electric field strength and the characteristics of nanoparticles. The sensor with controllable film and high repeatability possesses high sensitivity up to 5334 nm/RIU theoretical and 4704 nm/RIU experimental, which provides information for utilization of nanoparticles in LMR sensing. • A novel SnO 2 lossy-mode resonance fiber optic sensor utilizing SnO 2 nanoparticles is proposed. • The sensors possess sensitivity up to 5334 nm/RIU theoretical and 4704 nm/RIU experimental. • Firstly apply layer-by-layer method to fabricate SnO 2 LMR sensors. • Explore the relationship between sensitivity of LMR sensors and thickness of film. • Study the sensitization of SnO 2 NPs to SnO 2 LMR sensors. [ABSTRACT FROM AUTHOR]

This paper provides an updated literature review about greenhouse systems and helps to identify the most preferable characteristics of a greenhouse for diverse climates and operating conditions. Data on appropriate properties of the covering materials and comparisons of several cladding materials were extensively discussed. The selection process of the greenhouse shape and orientation for different climates is presented, and comparisons between several shapes and orientations are made. This paper also examines the existing thermal models and simulation tools used to optimize the thermal operating conditions of the greenhouse. Furthermore, many recent studies are presented where greenhouses are combined with several systems to provide a favorable microclimate for crops, under extreme, tropical and subtropical climates. Finally, other applications such as greenhouse dryers and seawater greenhouse desalination are also discussed. [ABSTRACT FROM AUTHOR]

This paper presents a critical advancement in Building Energy Modeling (BEM) through an empirical validation approach using a high-quality dataset from a multizone commercial office building in Oak Ridge, TN, USA. BEM is widely utilized in diverse construction applications, but its effectiveness relies on the accuracy of its predictions. The study focuses on empirical validation of input parameters in BEM, including building envelope data, infiltration modeling, and rooftop unit system performance curves. The validation of simulation input parameters leads to substantial improvements in the accuracy of simulation results. Notable both NMBE and cv (RMSE) values are reduced by 0.5 % for indoor air temperature and 17 % for indoor air relative humidity compared to the previous model. At the system level, both NMBE and cv (RMSE) values are reduced by 2 % for fan energy consumption and 4 % for cooling energy consumption, compared to the previous model. A literature review highlights a significant gap in empirical validation studies, which predominantly concentrate on either component-level or whole building validation. Furthermore, many studies employ simplified setups that may not faithfully represent the complexities of multizone commercial buildings. This paper distinguishes itself by emphasizing the critical importance of component-level input parameter validation. It underlines the need to validate data related to building envelope components and HVAC system performance curves, resulting in more accurate simulation outcomes. The utilization of actual multizone commercial building data enhances the study's practical relevance. In summary, this research underscores the pivotal role of input parameter validation in enhancing the accuracy and reliability of BEM. • The EnergyPlus simulation model input parameters have been empirically validated. • Building envelope input parameters have been evaluated. • Tracer gas and blower door tests have been performed to update infiltration model. • The rooftop unit performance curve has been developed using field datasets. • The simulation results are well-matched with field data at zonal- and system-level. [ABSTRACT FROM AUTHOR]

Excavation on jobsites is a collaborative effort, with a spotter serving as an extra set of eyes for the operator to ensure safety. However, current training methods using simulators are limited in immersion and primarily designed for individual operators to practice basic skills. This paper presents a multi-user teleoperation system featured with hybrid-immersive interface and between-user communication. The effectiveness of the system is evaluated through human subject experiments. The study's findings indicate that operators experienced greater immersion, a stronger sense of presence, and improved user interaction when using an immersive interface. This paper has important implications for the future of excavation training, with potential benefits including reduced utility strike damage and the opportunity to investigate human-robot collaboration in jobsites with multiple workers performing various roles within a highly immersive operational environment. • A multi-user excavator simulation system composed of robotic control, motion capture, and hybrid-immersive interfaces. • Human subject experiments with 57 subjects to evaluate the proposed system. • The effectiveness of the system is validated by achieving higher performance metrics than the monitor-based system. • Task completion time, accuracy, and safety are significantly improved under collaborative operation with a spotter. • Enhanced human factors study of the multi-user interaction with multi-roles in the human-robot collaboration in jobsites. [ABSTRACT FROM AUTHOR]

• The numerical model's setup for the steel fibre reinforced concrete (SFRC) segment. • Numerical simulations of GPR detection for SFRC segment under different conditions. • Optimum frequency selection of the SFRC segment. • Validation of an SFRC segment detection based on a model test. • Calculation of the equivalent relative dielectric constant (ERDC) of SFRC segments. The SFRC segment is gaining attention in shield tunnels due to their better mechanical properties. However, the existence of steel fibres poses a greater difficulty when attempting to utilize ground penetrating radar (GPR) for nondestructive quality inspection compared to conventional reinforced concrete segments. This paper presented a refined numerical model of SFRC segments with gprMax software, to investigate the penetration characteristics of GPR. The numerical model incorporated four different steel fibre contents, namely 0%, 0.5%, 2.5%, and 5%. The model also included an internal void and a surface metal plate to compare and analyze the waveform characteristics of GPR with the normal sections of the segment. The orthogonal test of numerical simulation investigates the imaging characteristics, power attenuation patterns, and imaging features of three different GPR frequency gradients: 200 MHz, 500 MHz, and 1000 MHz. This analysis helps in selecting the appropriate detection frequency based on the observed energy attenuation patterns and imaging characteristics. Then, the model test was conducted at the selected frequency to study the penetration performance of GPR. The research results indicate that the numerical model established in this paper demonstrates good effectiveness in studying the waveform characteristics of steel fibre-reinforced concrete under various conditions. The numerical model established in this paper realized the study of the penetration characteristics and imaging features of different steel fibre contents, GPR frequencies, and detection targets. Analysis of waveform characteristics, power attenuation, and imaging results indicates that GPR at 500 MHz exhibits better detection performance for SFRC segments. The results of the numerical simulation were verified through model tests of real SFRC segments, demonstrating that 500 MHz has good penetration performance for SFRC segments. This paper also proposed a calculation method for equivalent relative dielectric constant (ERDC) based on the model test results and validated its rationality through the analysis of numerical simulation results and real GPR waveforms. [ABSTRACT FROM AUTHOR]

Distribution networks aim to get the right products to consumers at the right time and in the right place. When consumers return these products, another type of logistics network is involved. This function of returning end-of-life products is referred to as reverse logistics. A critical characteristic of these reverse logistics networks is the dependence of material flow on the voluntary action of the consumer. Therefore, the success of an end-of-life collection strategy depends on the ability to anticipate the collection rate of end-of-life products at specific locations by understanding the factors that influence consumer behavior. However, there is no established tool or methodology for assessing the impact of consumer decisions on reverse logistics material flows. Therefore, this paper proposes an agent-based simulation tool to predict the performance of a reverse logistics network, taking into account the location of collection points, socio-demographic information, attitudes towards sustainable development, as well as the consumption profile. More specifically, this paper presents the configuration, calibration and validation of a simulation tool modelling the return of empty glass bottles in a small group of municipalities in Québec, Canada. Experiments also demonstrate the tool's ability to provide useful information to support the design of collection strategies that maximize return rates while minimizing installation and operating costs by optimizing the number of drop-off depots in the reverse logistics network. • Drop-off points for post-consumer voluntary glass collection. • Agent-based simulation model of consumer waste management (at consumer level). • Configuration, calibration and validation of a simulation model with empirical data. • Experiments performed with the model evaluates different logistics configurations. • Results suggest that population-specific characteristics can influence return rates. [ABSTRACT FROM AUTHOR]

Second-order macroscopic continuum models have been constantly improving for decades to reproduce the empirical observations. Recently, a series of experimental studies have suggested that the stochastic factors contribute significantly to destabilizing traffic flow. Nevertheless, the traffic flow stability of the stochastic second-order macroscopic continuum model has not received the attention it deserves in past studies. More importantly, we have found that the destabilizing aspect of stochasticity is still not correctly validated in the existing theoretical stability analysis. In this paper, we analytically study the impact of stochasticity on traffic flow stability for a general stochastic second-order macroscopic model by using the direct Lyapunov method. Numerical simulations have been carried out for different typical stochastic second-order macroscopic models. Our analytical stability analysis has been validated, and our methodology has been proved more efficient. Our study has theoretically revealed that the presence of stochasticity has a destabilizing effect in usual stochastic macroscopic models. • Stability condition of a general stochastic second-order macroscopic continuum model. • The Lyapunov method outperforms the eigenvalue method. • The stochastic macroscopic models respond differently to the presence of stochasticity. • The presence of stochasticity has a destabilizing effect in usual stochastic macroscopic models. [ABSTRACT FROM AUTHOR]

Shallow geothermal offers great potential to supply emission-free heating and cooling and has therefore a pivotal role in the transition of heating and cooling networks. This paper presents a novel heating and cooling network with possible geothermal energy sharing between decentralized borefields located at each building level. The system consolidates the benefits of both standalone and centralized energy systems to attain high-efficiency gains and ensure a secure heating and cooling supply. To study the expected system performance, a simulation model is demonstrated and applied to a real-world case study consisting of three new buildings located in Malmö, Sweden. Simulation results revealed that the established synergy through geothermal energy sharing can reduce the purchased electric energy by 23 % and increase the annual performance factors for heating and cooling by 31 and 35 %, respectively compared to the standalone system. [ABSTRACT FROM AUTHOR]

The diffusion-absorption refrigerator (DAR) is a cooling technology that can be driven entirely by thermal energy. With solar-thermal collectors as the heat source, this technology can provide a zero-emissions solution for essential cold-chain provision in the world's poorest regions. In the accompanying paper, a system model of a solar-driven DAR system was developed for simulating operation under variable solar conditions. In Part II of this study, we apply this model to assess the predicted performance of the system in its intended application: for on-farm refrigeration of harvested crops in rural India. The roles of the working-fluid charge pressure and collector array area for maximum cooling are investigated. A charge pressure of 16 bar is found to be optimal for ambient conditions during the October harvest season in Ahmedabad, with a collector-array area of 1.5 m2 found to be most appropriate for the nominal 70 W cooling-capacity system. However, the time taken to reach the required solar collector temperature for bubble pump activation results in a daily operating period of less than 5 h and a predicted overall solar-to-cooling efficiency of less than 1%. To address these limitations, modifications to various components are considered based on simple assumptions for improving performance. • An assessment is performed of a solar diffusion absorption refrigeration system. • Off-grid cooling operation is simulated for the target region of Ahmedabad, India. • A cooling output of 170 kJ/day is predicted with a solar collector area of 1.5 m 2. • An optimal charge pressure of 16 bar is determined for maximum cooling output. • Modifications to key system components are recommended based on the results. [ABSTRACT FROM AUTHOR]

• A new comprehensive AC power flow-based framework for cascading outage simulation is proposed. • The islands created at a simulation stage are accurately identified using a new algorithm called linear dependency-based islanding detection. • A new algorithm is proposed to handle the active power balance within each island considering all frequency controllers and generators power limits. • A new enhanced under-voltage load shedding is proposed to address voltage instability. • An extended AC power flow is proposed as the core of the simulator, considering generators participation to frequency control and voltage dependant loads. Simulating accurately and fast cascading outages play a critical role in power system security and resilience assessment. This paper proposes a new comprehensive framework for cascading outage simulation, articulated around an extended AC power flow. To address the key modelling features of cascading outage simulation, the proposed framework develops new algorithms for: a) detecting possible islanding, b) frequency control in each island: primary frequency control (PFC), under-frequency load shedding (UFLS) and over-frequency generator tripping (OFGT) and c) improved under-voltage load shedding (UVLS) and load models to avoid the divergence of AC power flow and allow handling voltage instability during the cascade. Tests on a realistic 60-bus system show that the proposed cascading outage simulator can successfully handle islanding, PFC, UFLS, OFGT, and UVLS; it simulates the cascade until there is no violation of system frequency, voltage, and power flow limits in islands that do not experience blackout. [ABSTRACT FROM AUTHOR]

Indole-based bis-acylhydrazone compounds can inhibit the activity of α-glucosidase and control the concentration of blood glucose. In this paper, the characteristics of three indole-based bis-acylhydrazone compounds with different inhibitory activities of α-glucosidase as well as the interaction with α-glucosidase were studied by experiments and computational simulation techniques. Enzyme kinetic and spectral experiments showed that the indole-based bis-acylhydrazone compounds were able to inhibit enzyme activity through mixed inhibition dominated by competitive inhibition, and during the binding reaction, indole-based bis-acylhydrazone compounds can quench the intrinsic fluorescence of α-glucosidase through static quenching and an aggregation of the indole-based bis-acylhydrazone with α-glucosidase produces a stable complex with a molar ratio of 1:1, and the combination of indole-based bis-acylhydrazone compounds could lead to slight change in the conformation of α-glucosidase. The theoretical simulation demonstrated that the stability of the complex systems was positively correlated with the inhibitory activity of indole-based bis-acylhydrazone compounds, and the indole-based bis-acylhydrazone compounds occupied the active site in the multi-ligand system, resulting in a significant decrease in the binding ability of starch to active amino acids. These results suggested that indole-based bis-acylhydrazone compound was expected to be a new type of α-glucosidase inhibitor. • Three indole-based bis-acylhydrazone compounds (A, B and C) inhibit α-glucosidase in the mixed inhibition mode. • The binding mechanism of compounds were analyzed by experiments and simulation. • Relationship between inhibitory activity and binding characteristics of compounds A, B and C • Compounds A, B and C occupied the active site of α-glucosidase. [ABSTRACT FROM AUTHOR]

The metering mode is gradually changing from volumetric metering to energy metering under the open-access operation of gas pipelines. The gas component tracking by operating simulation is an effective method to realize the energy metering of gas networks. In this paper, coupling and decoupling transient component tracking models of gas networks are proposed. The pipeline governing equations, compressor equations, valve equations, and node relationship equations are considered in the proposed models. The implicit central difference method and the damped Newtonian method are adopted to solve the models. The coupling model considers the component tracking part and hydraulic-thermal simulation as a whole, while the decoupling model splits the whole process into the gas component tracking part, the parameters calculation part, and the hydraulic-thermal simulation part. In the component tracking part, the spatiotemporal variation of the gas mass fraction and density can be obtained through the input velocity of each node. Then, the parameters in the gas state equation can be solved, the hydraulic-thermal simulation can be performed, and the new velocity of each node can be calculated. The iteration for each time step ends if the deviation of flow velocity in the component tracking process and the hydraulic-thermal process satisfies the requirements. Two cases are studied to verify the effectiveness of the proposed models, and the boundary condition adaptability of the transient simulation models is analyzed. The proposed models can efficiently simulate the spatiotemporal variation of the operating variables and gas components, providing a reference in the operation of natural gas pipeline networks. [Display omitted] • The most accurate gas state equation with 11 parameters is chosen in the models. • A coupling model integrating the T-H process and the GCT process is proposed. • The T-H and GCT sub-models are decoupled to establish the decoupling model. • The proposed models are applied to different boundary conditions combinations. [ABSTRACT FROM AUTHOR]

The calculation of the temperature fields in solid state transformers is a critical step of the design process in order to ensure the stable and efficient operation of the device. Transformers operating in high frequencies can develop increased temperatures that potentially may result in the failure of the components due to the associated thermal stresses. This paper investigates the heat transfer mechanisms of a novel inductive power transfer (IPT) system submerged in a dielectric oil and operating at 50 kHz, in the context of SSTAR, a Horizon Europe project. The commercial software ANSYS is employed to implement a one-way coupled electromagnetic-thermal finite element simulation model in order to calculate the temperature field of the IPT components based on the electromagnetic losses. To cross-validate the model, the results obtained from ANSYS are benchmarked against the COMSOL software, revealing accepted temperature deviations between the two software. A comprehensive parametric analysis explores the impact of rated power, operating frequency, and dielectric gap on generated heat, highlighting their direct correlation with temperature increase. The findings underscore increased temperature levels, approximately reaching 224 °C under nominal operating conditions, with the temperature distribution concentrated around the transformer's windings. • Design of a novel high frequency 50 kHz Inductive Power Transfer system. • Assessment of the heat transfer mechanism of an Inductive Power Transfer system. • Development of a comprehensive coupled electromagnetic-thermal simulation model and validation. • Parametric analysis on the effect of rated power, frequency and dielectric gap on power loss and temperature. [ABSTRACT FROM AUTHOR]

In this paper we present a scalable approach based on the latency-based linear multistep compound method to use graphic processing unit (GPU) to accelerate the power system simulations with electromagnetic transients. To balance between the computational load and accuracy, we modeled the power system using shifted frequency analysis. Then, to efficiently exploit the hardware, our computational approach is designed to utilize both data-parallel and task-parallel execution. In addition, a graph-based thread safety design is introduced to achieve high scalability in the paralleled component computations. Furthermore, our implementation introduces a translation layer for different heterogeneous computing frameworks during compile time, so that a wide range of GPU devices can be supported without losing performance. Finally, benchmark results show that our approach achieves faster-than-real-time capability for systems with hundreds to thousands of nodes. [Display omitted] • Exploits data- and task-parallelism together in an automated way. • A graph-based approach to ensure thread safety to increase scalability. • A compile-time translation layer to allow execution on various platforms. • Faster-than-real-time for system with more than 10,000 dynamic components. • 82 × faster compared to an optimized sequential simulation. [ABSTRACT FROM AUTHOR]

The Full of Economic-Environment Linkages and Integration dX/dt (FeliX) model is a System Dynamics-based Integrated Assessment Model (IAM), explicitly incorporating human behaviors and their dynamic interactions among global systems. This paper presents FeliX 2.0, describing the detailed framework and key interactions among nine integrated modules. FeliX 2.0 refined its original version in population dynamics, food and land use systems, and socioeconomic settings for poverty analysis. Robust calibration is applied to key variables against their historical data since 1950. Future projections of multiple variables up to 2100 demonstrate coherences between FeliX 2.0 and the IAMs used in IPCC assessments. Both outputs (the robust calibration results and future projections) underscore the efficacy of FeliX 2.0 in capturing complex interdependencies within global systems. FeliX 2.0 stands as an informative tool and offers insights into interactions within the human-Earth system and the analysis of complex economic-environmental-social challenges in short- and long-term future. • A SD-based IAM model—FeliX 2.0—integrating human behavior for the human-Earth system simulation. • FeliX 2.0 refines FeliX 1.0 in population dynamics, food and land use, and poverty modeling. • Coherent projections up to 2100 for key variables in human-Earth systems by FeliX 2.0 • FeliX 2.0 stands as a pioneering tool for analyzing economic, environmental and social challenges. [ABSTRACT FROM AUTHOR]

Flexible DC Transmission Systems (FDCTS) devices offer the most promising solution for Power Flow Management (PFM) problem in complex meshed MTDC grids. This paper proposes a new formulation for steady state analysis of a MTDC grid, integrated with the multiport version of the FDCTS device called Multiport Interline DC Current Flow Controller (MIDCCFC). MIDCCFC can regulate the current flow of two or more lines, thereby achieving line power flow regulation and aid for DC line breaking in a MTDC system. The proposed formulation integrates the steady state operating point of MIDCCFC with the MTDC system. The proposed formulation is tested on a 5 bus 320 kV meshed MTDC grid with 5-port MIDCCFC. A criterion is evolved to ensure the feasibility of the operating point obtained from the proposed formulation. The line current regulation range offered by MIDCCFC for line-12 in the test system is (30-3086) A. The impact of line-12 current variation on the system variables over the obtained range is investigated. The application of MIDCCFC for DC breaking is also investigated. The results are validated by performing steady state simulation of the test system in MATLAB/Simulink and real time simulation of the test system in Real Time Digital Simulator. [Display omitted] • Formulation of Power flow model for MIDCCFC integrated meshed MTDC system. • Application of Newton–Raphson based iterative algorithm for DC power flow analysis of MTDC system with MIDCCFC. • Criteria for feasible existence of the steady state operating point. • Validation of the power flow results in real-time using Real Time Digital Simulator (OP4510). [ABSTRACT FROM AUTHOR]

• Event-triggered secondary controllers under multiple delays are discussed. • Compared with traditional event-triggered and dynamic event-triggered, the proposed scheme has high accuracy in tracking voltage and frequency setpoints, and can effectively reduce the communication burden and maintain the system performance. • The proposed controller is robust to external disturbance and multi-delay. The stability of the proposed control strategy is proved using the lyapunov method. In this paper, an adaptive event-triggered H ∞ consensus control scheme is proposed for the secondary layer of AC MGs. The controller design problem of topological communication network with external disturbance, multiple delay, and communication burden is considered. Therefore, using the Lyapunov-Krasovskii theory, we obtain sufficient conditions for the robust consensus convergence of multi-agents under event-triggered and multiple time delays. Because traditional event-triggered often use fixed thresholds, it is challenging to balance reducing the communication burden and maintaining excellent system performance. Therefore, we design an adaptive event-triggered method that adaptively adjusts the trigger threshold according to the consistency error. Finally, a simulation system is established. The proposed control strategy has been validated through simulation results. [ABSTRACT FROM AUTHOR]

The supporting structure's dynamic stiffness has an important influence on the rotor system. However, current research is mainly limited to the stiffness of a single supporting structure. A single supporting structure may not meet the requirements of the rotor system in some cases. Therefore, the method of solving dynamic stiffness of combined supporting structure is presented and compared with the traditional method based on the parallel stiffness formula. The correctness of the proposed method is verified experimentally. Then, the model of rotor system is established that takes into account the combined supporting structure's dynamic stiffness. Finally, the variation of rotor system's critical speeds and vibration response under the influence of dynamic stiffness is analyzed. An experiment is carried out to verify the influence of dynamic stiffness on the critical speeds. Furthermore, the critical speeds of rotor system will decrease under the influence of dynamic stiffness. • This paper presents a dynamic stiffness model of the combined supporting structure. • The accuracy of the proposed model is validated by experiment. • The rotor system model considering dynamic stiffness is established. • The effect of dynamic stiffness on the rotor system is verified by numerical and experimental studies. [ABSTRACT FROM AUTHOR]

Pedestrian modeling and simulation has become an interesting topic that has gained scientists' interest over the past few decades. While this field has yielded significant achievements in various applications, questions have been raised regarding the applicability of simulations in high-density scenarios. To this purpose, this paper comprehensively reviews pedestrian simulation models specifically focused on high-density situations. The review examines a total of 116 articles and categorizes their approaches for modeling pedestrian behaviors to different decisional levels. The strengths and limitations of these modeling approaches are compared and evaluated using different criteria for dense crowd simulations, such as their ability to simulate common emergent behaviors in crowded situations, performance, validation, and capacity to integrate into high-level modeling. Finally, the review provides potential directions for future research and development of dense crowd simulations. • Conducting a systematic review of existing approaches for dense crowd simulation. • Investigating pedestrian simulation models at different behavioral levels. • Comparing various models using multiple criteria tailored to high-density situations. • Analyzing the advantages and drawbacks of simulation models in crowded settings. [ABSTRACT FROM AUTHOR]

A Non-Fungible Token (NFT) is a digital asset that is proof of ownership and originality in the digital world. It is generally a unique data unit that can be created from a digital file. But it is not just any digital file; it must be audio, video, image, or photo. This fact is mainly limiting. However, there are many other digital files for which the connection with NFT and blockchain technology would make sense. Such digital files include, among other things, various simulation models. With the development of the use of simulation models for the needs of managing multiple types of logistics processes daily, the questions of how to prevent the unauthorised copying of any simulation model and protect the copyright of its authors are coming to the fore. NFT and blockchain represent a robust technology whose possibilities of use are gradually expanding, while simulation models could be one area of their application. The paper presents the result of research that will enable the implementation of NFT and blockchain technology in simulation models. The research outcome confirmed the possibility of creating an NFT through the decentralised public blockchain XRP Ledger (XRPL) and the marketplace xrp. cafe, which can be used to verify the ownership and originality of the simulation model. [ABSTRACT FROM AUTHOR]

Ocean renewable energy, such as wave and tidal energies, is important for energy supply and decarbonization of offshore platforms and ships. However, the intermittent and non-dispatchable nature of wave and tidal energy remains a significant challenge. The hybrid wave-tidal energy conversion presents a potential solution to enhance output power and stability by leveraging their complementary characteristics. This paper reviews the current state of hybrid wave-tidal energy conversion technology, focusing on device design, modeling methods and testing methods. Many current hybrid wave-tidal energy converters (HWTEC) have not considered effective coupling among the modules of sub-systems to maximize efficiency. Modeling and simulation methods are mainly based on studies of single wave or tidal energy conversion, and non-linear system modeling is rare. The assumption of continuous functions in most models can lead to discrepancies from real-life conditions. Advancement of modeling approaches, co-simulation algorithms, and dedicated dry lab and pool tests for HWTEC are desired. While HWTEC is potential for improving ocean energy conversion, addressing key challenges of device design, modeling, testing and economic evaluation are essential for realizing its full potential in contributing to decarbonization. • Wave and tide are compared from the perspective of hybrid energy conversion. • Hybrid wave-tidal energy converters are classified and reviewed. • Analysis methods for hybrid wave-tidal energy converters are summarized. • Technology gaps in hybrid wave-tidal energy conversion are identified. • Potential research directions of hybrid wave-tidal energy conversion are proposed. [ABSTRACT FROM AUTHOR]

• A disturbance simulation model of tooth-flexible body residual film-soil based on DEM-MBD was established. • The flow characteristics of film-soil was studied using DEM-MBD simulation methods. • A film picking test bench was established to verify the reliability of the simulation model. • The cross-sectional shape of soil was used to verify the accuracy of DEM simulation models. • The mechanical properties and tensile performance of the residual film were analyzed. The residual film in the cotton cultivation layer will seriously affect cotton cultivation, and mechanized recycling of residual film is currently the best way to solve this problem. To improve the recovery effect of the chain tooth tillage layer residual film recovery machine, a bionic elastic tooth was designed in this paper. Furthermore, DEM-MBD coupling multibody dynamics was used as the research method to study the bionic elastic tooth-residual film-soil interactive disturbance. A DEM-MBD simulation model for predicting the film lifting effect of a film lifting device has been established. And the DEM-MBD simulation model was used to optimize the design parameters of the film lifting device by studying the film lifting effect of the elastic teeth. The absolute value of the maximum curvature at the tip of the elastic tooth (A), the angle between the midline of the power wheel and the ground plane (B), and the spacing of the elastic teeth (C) were used as the influencing factors. The optimal solution parameters (A = 0.03, B = 54°, C = 83 mm) were obtained. The field test's film picking and disturbance rate was 91.27 %, the error with the simulation results (89.69 %) was 1.8 %, which verified the accuracy of the simulation results and the superiority of the optimized parameters. The recovery rates of residual film under soil compaction conditions of 600 kPa, 800 kPa, and 1000 kPa were 91.25 %, 90.94 %, and 90.89 % (Verified the strong adaptability of the device). This study can provide a theoretical research basis and test methods for the design optimization of touching parts. [ABSTRACT FROM AUTHOR]

The computational fabrication community is developing an increasing interest in the use of patterned surfaces, which can be designed to show ornamental and unconventional aesthetics or to perform as a proper structural material with a wide range of features. Geometrically designing and controlling the deformation capabilities of these patterns in response to external stimuli is a complex task due to the large number of variables involved. This paper introduces a method for generating sets of tileable and exchangeable flat patterns as well as a model-reduction strategy that enables their mechanical simulation at interactive rates. This method is included in a design pipeline that aims to turn any general flat surface into a pattern tessellation, which is able to deform under a given loading scenario. To validate our approach, we apply it to different contexts, including real-scale 3D printed specimens, for which we compare our results with the ones provided by a ground-truth solver. [Display omitted] • Patterns are interesting from a visual and a mechanical perspective. • Their computational design is complex and an intriguing task. • We provide an efficient simulation model with our generated flat patterns. • Pipeline for direct design of tiled patterns' assemblies. • Design exploration with an interactive tool that manages geometry and loads. [ABSTRACT FROM AUTHOR]

Constructing simulation models can be a complex and time-consuming task, in particular if the models are constructed from scratch or if a general-purpose simulation modeling tool is used. In this paper, we propose a model construction framework, which aims to simplify the process of constructing discrete event simulation models for emergency medical service (EMS) policy analysis. The main building blocks used in the framework are a set of general activities that can be used to represent different EMS care chains modeled as flowcharts. The framework allows to build models only by specifying input data, including demographic and statistical data, and providing a care chain of activities and decisions. In a case study, we evaluated the framework by using it to construct a model for the simulation of the EMS activities related to acute stroke. Our evaluation shows that the predefined activities included in the framework are sufficient to build a simulation model for the rather complex case of acute stroke. [ABSTRACT FROM AUTHOR]

Ethylene and propylene are among the light olefins which are the main building blocks in the petrochemical and chemical industry. They are produced from thermal/catalytic cracking of gaseous and liquid hydrocarbons and recently from methanol. This paper continues the two review articles published before entitled thermal and catalytic cracking of hydrocarbons for the production of light olefins. In the last two review articles, the processes and the kinetics of thermal and catalytic cracking have been discussed in details. This paper reviews the mathematical modeling and simulation of the olefin plants including mechanisms and kinetic models, CFD simulations, rigorous models, and abstract models. [ABSTRACT FROM AUTHOR]

• A novel application of SFO algorithm to extract PV model parameters is presented. • Three-diode PV model is used in this paper. • Parameters of SFO-TDPV model are compared with other optimization based models. • The SFO-TDPV model is verified by comparing its results with measured data. • The error among these results records a value less than 0.5%. This article proposes an accurate and straightforward method for modeling and simulation of photovoltaic (PV) modules. The main target is to find the nine-parameter of a three-diode (TD) model based on the datasheet parameters, which are given by all commercial PV modules. The objective function is formulated based on short circuit, open circuit, power derivative, and maximum power equations. Two parameters (parallel resistance and photo-generated current) are calculated analytically and rest parameters are optimally designed using the sunflower optimization (SFO) algorithm. The presented method is applied to model three types of commercial PV modules (multicrystal KC200GT, poly-crystalline MSX-60, and mono-crystalline CS6K-280M). The optimal nine-parameters obtained in this paper are paralleled with that attained by other approaches. In order to assess the efficiency of the offered approach, I-V and P-V characteristics are validated with measured data under various temperatures and solar irradiations. The error among these results records a value less than 0.5%. Therefore, the simulation results indicate an excellent agreement with the measured data. This proposed approach can be utilized to model any marketable PV module based on given datasheet parameters only. [ABSTRACT FROM AUTHOR]

• Credit risk migration rates matrices with entries, migrations of stayers and exits are simulated. • A mathematical procedure to extrapolate future dynamics conditional to a macroeconomic scenario is developed; • IFRS9 segmentation into buckets and prospective estimates of Expected Loss are introduced. In 2014 the International Accounting Standards Board (IASB) promulgated the current International Financial Reporting Standards 9 – Financial Instruments (IFRS9) that draw new lines for an ex-ante , reliable, unified and well-balanced credit risk assessment. Among others, two principles are of interest to this paper: that of segmented and prospective estimation of expected credit losses. Within the frame of a micro-simulation approach, this paper focuses on these issues while considering the evolution of a bank portfolio. The paper presents an algorithmic procedure developed on a realistic dynamic credit risk migration rates modelling of a portfolio as an open system with entries and exits that is consistent with the segmented and prospective IFRS9 principles. Although operating at the aggregate level of the migration matrix, combining accounting principles inspired to those of the IFRS9-baseline with the open systems modelling, the main conclusion is that it allows for a more reliable provision and ex-ante and forward-looking estimation of expected losses. [ABSTRACT FROM AUTHOR]

The authors have attempted to summarize the evolution of research in Construction Productivity (CP) through a Systematic Literature Review (SLR) from the papers published from 2006 to 2017. The methodology adopted for the study is to use the systematic literature review for selecting the papers published in a few selected major journals of construction, built environment, and construction management fields. A total of eight journals selected for the SLR and 101 papers have been selected using the keyword "Construction Productivity in the title or the Keywords". The findings of the study conclude that the studies in CP are focused in seven main areas are industry-level studies, the study of factors/attributes, measurement techniques, simulation and models, equipment and technology, issues and problems associated with CP, and improvement techniques and proposed frameworks. [ABSTRACT FROM AUTHOR]

• This paper presents an agent-based simulation model to investigate the performance of traffic during post disaster reentry for the Gulf Coast megaregions. • This research shows that reentry traffic processes behavior similar to, but in the reverse direction of evacuations. • The heterogeneity of traffic flow distribution is the main reason that determines the network performance for any set of conditions. • Prolonging departure time range would not always benefit the network performance and an acceptable departure time range will benefit the reentry process while not waste public resources. Transportation personnel, assets, and systems play important roles during emergencies. Of particular note is the critical function of road networks as lifelines for evacuations, then, after such events, to facilitate the rapid inflow of support personnel and resources needed to assess and repair damage. They also provide access for the safe and rapid return of evacuees. Despite the importance of reentry and repopulation, the role of transportation systems for them has been a relatively lightly researched topic. This paper describes research to analyze the traffic processes associated with post-evacuation reentry and its associated travel time and delay. To examine the most extreme of conditions; this effort also focused on repopulation and reentry after mass evacuations in megaregions. Among the findings of this work were that, as expected, reentry traffic processes generally behave similar to, but in the reverse direction, of evacuations. However, contrary to commonly held belief, they are not identically opposite. Rather, network performance during reentry may often be better than that of evacuation. Another broad finding of the research was that the spatial heterogeneity of traffic distribution across available roadways is a primary factor in determining network performance, meaning the more uniform the spread of on all links, the more efficient the network will operate. A third significant finding of this research was also the importance of the temporal spreading of returnee departure times on network efficiency. [ABSTRACT FROM AUTHOR]

The electricity industry consists of multiple parties on generation, transmission, distribution, trading and market supervision of electricity. Models for a single electricity firm are only suitable for studying the operational decisions of the particular firm. In order to study the bidding behavior of all the players in the electricity market, this paper proposes a hybrid simulation model (HSM) that combines agent-based simulation (ABS) and system dynamics simulation (SDS). With the proposed hybrid model, some input variables required for one simulation model can be obtained by the output of another simulation model. In order to improve the competitiveness of agents that participate in bidding, this paper incorporates the Reinforce Learning (RL) algorithm into the agents. Each agent can obtain information and adapt to the environment through the continuous interaction with the environment. With the hybrid simulation model, the dynamics of the entire market remain stable, the market clearing prices converge, and the market share is relatively uniform. • The bidding of all the players in the electricity market is multilateral bidding. • Macro whole bidding in the electricity market simulated by system dynamics. • Micro detail biding of in the electricity market simulated by multi-agents. • The competitiveness of bidding agents improved using reinforce learning algorithm. • Multilateral bidding simulated combines agent and system dynamics based simulation. [ABSTRACT FROM AUTHOR]

• A generalized nonlinear distribution parameter model of DSG collector is established. • A unified formulation of fluid thermodynamic properties in DSG loop is constructed. • A FPT algorithm to determine the transient change of the properties and phase transition points is developed. • The dynamic characteristics of a once-through DSG collector system are studied. Heretofore, studies about the modeling and simulation of Direct Steam Generation (DSG) process in parabolic trough solar collector (PTC) system are based on the spatial control volume modeling that belongs to Eulerian method. The moving boundary model is applied for the single-phase and two-phase fluid respectively. The model and the related algorithm lack necessary generality. Moreover, when system operating conditions change dramatically, the model's numerical stability is difficult to be guaranteed. For this, based on the idea of fluid parcel-tracking (FPT) of Lagrange approach, modeling and simulating the DSG dynamic process in PTC system under once-through mode are studied in this paper. A unified formulation of the variation of fluid thermodynamic properties in the absorber is built. Then, a generalized one-dimensional distribution parameter model of fluid heated and phase-change process is established. A FPT algorithm corresponding to the model is developed, by which the transient distributions of fluid thermodynamic properties and the transient position of fluid phase-change point are obtained. Additionally, the model and algorithm are primarily verified by existing experimental results. Finally, simulation experiments are carried out for studying the transient distributions of fluid thermodynamic properties in absorber under typical input disturbances, and for displaying the disappearance and regeneration process of the superheated region and two-phase region under large direct normal irradiance (DNI) disturbance. Results show that the presented model and calculation method have good versatility and can simulate the dynamic process of the DSG system. This paper possesses practical value for real-time analysis, controller design and assessment of the DSG system. [ABSTRACT FROM AUTHOR]

The estimation problem for stochastic parametric nonlinear dynamical models is recognized to be challenging. The main difficulty is the intractability of the likelihood function and the optimal one-step ahead predictor. In this paper, we present relatively simple prediction error methods based on non-stationary predictors that are linear in the outputs. They can be seen as extensions of the linear prediction error methods for the case where the hypothesized model is stochastic and nonlinear. The resulting estimators are defined by analytically tractable objective functions in several common cases. It is shown that, under certain identifiability and standard regularity conditions, the estimators are consistent and asymptotically normal. We discuss the relationship between the suggested estimators and those based on second-order equivalent models as well as the maximum likelihood method. The paper is concluded with a numerical simulation example as well as a real-data benchmark problem. [ABSTRACT FROM AUTHOR]

Abstract New requirements on post-accident monitoring systems in nuclear power plants pose fresh challenges for electronic system designers and nuclear power plant personnel, in particular, on how radiation can potentially affect the electronics in such systems; and how one can deal with such effects. In fact, study on radiation effects on electronic devices, effective design techniques to reduce such impacts, as well as simulation tools and design aids, has spanned for many decades. As a result, there is vast literature on the subject scattered in many places and in various forms, which inadvertently makes it difficult for non-specialists, such as an electronic engineer, to obtain relevant information effectively. The objective of the current paper is to provide a high-level overview in an organized fashion to guide readers to right literature for more detailed study on a specific topic in this area. The paper consists of three logically connected parts: radiation effects on electronics; design techniques to minimize such effects; and modeling and simulation tools available. For each part, a brief introduction of key issues is described first followed by a list of key references. In total, 336 references have been assembled to provide a comprehensive coverage on this subject. Highlights • Overview of radiation effects on electronic devices under severe accident conditions in NPPs. • Overview of rad-hardened design techniques and simulation tools. • In total, 336 references have been assembled. • References have been categorized logically for easy search. [ABSTRACT FROM AUTHOR]

Vehicular communication is characterized by a dynamic environment and high mobility. In this paper we present a shadow fading model targeting system simulations based on real measurements performed in underground gallery. As first results, we present in this paper the delay spread statistics for each investigated environment. We also study the large-scale, small-scale fading and extract some time channel parameters such as root-mean-square (RMS) delay for a realistic underground propagation environment at 5.9 GHz. Since there are so far few published results for these confined environments, the results obtained can be useful for the deployment of vehicular-to-vehicular (V2V) and vehicular-to-infrastructure (V2I) communication systems inside underground mines galleries. [ABSTRACT FROM AUTHOR]

In order to solve the failure of traditional methods in the response prediction for the complex spacecraft under the wide frequency shock load, this paper provides the FE-SEA (Finite Element-Statistical Energy Analysis) hybrid modeling technique to improve the virtual mode synthesis and simulation (VMSS). Taking the L-shape typical structure as an example, the research is developed through the numerical analysis and experiment verification. In the FE-SEA hybrid model of the typical structure, the two honeycomb boards which have a higher modal density are built as the SEA model, while the connection beam that has a larger stiffness is established as FE model. And then the hybrid model is computed with the VMSS code, giving the transient response results. A shock experiment for the typical structure is carried out to verify the correctness of the methodology above. The results indicate that the numerical results have the similar trend and magnitudes with the ones of the experiment in time domain, and the shock response spectrum (SRS) of the numerical results can realize the ±6 dB tolerance limit compared with the experiment results. This paper finds that the FE-SEA hybrid modeling techniques for the typical structure can effectively overcome the problem of the dynamic differences between the substructures under the excitation of shock load, and the combination of FE-SEA and VMSS has the ability to predict the shock responses of the typical structure accurately. The research methods and conclusions achieved in this paper are expected to further extend to the shock response calculation of the complex spacecraft structures. [ABSTRACT FROM AUTHOR]

• System dynamics modelling and simulation research has a large potential contribution to transition research. • The paper discusses exemplary system dynamics research that is directly relevant to transition research. • The paper discusses the interface of case study and simulation research. • The paper discusses system dynamics research that corresponds to the micro, meso, macro levels of transition research analysis. Sociotechnical transitions is an emerging research area that uses several methods, amongst which case study and simulation models are often applied. This paper focuses on system dynamics modelling and simulation research and its potential contribution to transition research. Current system dynamics work comes from a wide range of disciplines and spans across the micro, meso, and macro levels which transitions are predominantly analysed along. This overlap carries considerable potential as a conceptual and theoretical basis for transition research. The paper explores this potential and provides a cursory exposition of system dynamics research and exemplary work that is directly relevant to transition research. It raises a number of points that indicate the potential of system dynamics for transition research in terms of methodology and case study research, the behavioural aspects of transitions, and particular subject areas that lie at the organizational field level: technology platforms, business models and organizational change. [ABSTRACT FROM AUTHOR]

A high-pressure chamber is the main equipment required for simulating deep-sea operational environment and used for evaluating the performances of underwater equipment such as underwater vehicles under a preset pressure so that the possible malfunctions could be alarmed before deep-sea commissioning. In this paper, due to its current unavailability, a high-pressure chamber with the maximum working pressure of 60 MPa was designed, which has the inner diameter of 3 m and the height of 4 m, possesses the video transmission function and allows most of the small-scale underwater vehicle's overall stability and capacity to be tested possible. To tackle the leakage and ensure the stability of the chamber, this paper proposes a novel sealing method, which adopts the combination of anti-shear block device and four O-ring seals and has the advantage of no need of manual pre-tightening and of sufficient shear resistance. The performance and strength analysis of the chamber were carried out by Ansys/Workbench finite element analysis software. Furthermore, The high-pressure chamber was manufactured and its experiment verification results indicate that with larger containment volume and more advanced control system it could work reliably, which made it feasible for its engineering application. • A high-pressure chamber is the main equipment required for simulating deep-sea operational environment. • With the maximum working pressure 60 MPa, the high-pressure chamber has the inner diameter of 3 m, the height of 4 m. • The chamber possesses the video transmission function. • The performance and strength analysis of the high-pressure chamber were carried out by Ansys/Workbench FEA.. • Both the simulation and the experiment show that the chamber works reliably and is feasible for engineering application [ABSTRACT FROM AUTHOR]

Highlights • The data model for point-like targets detection is converted to a scalar one. • Two new detectors are designed based on this scalar data model. • The PFAs and PDs of the two new detectors are analytically derived. • The new detectors are effective when finite secondary data is available. • The new detectors are robust in the mismatched case. Abstract This paper approaches the problem of detecting a point-like target in Gaussian background. The useful signal lies in an one-dimensional subspace spanned by a known steering vector. The Gaussian disturbance fills the whole observation space. Since the disturbance outside the signal subspace is unrelated to the decision result, it is eliminated by pre-multiplying the recorded data by the conjugate transpose of the steering vector in this paper. This preprocessing is not applied in the classical detectors, such as the generalized likelihood ratio test (GLRT), the adaptive matched filter (AMF), etc. This preprocessing results in a new scalar data model where the useful signal and disturbance lie in the same space. Based on this scalar data model, two new detectors are designed through the one-step and two-step GLRT, respectively. Their probabilities of false alarms and detections are derived analytically. The one- (two-) step GLRT-based detector has the (approximately) constant false alarm rate feature in the Gaussian background. Simulation results show that the proposed detectors outperform those classical ones when finite training data is available. The one-step GLRT-based detector is more robust to mismatched signals than those classical detectors. [ABSTRACT FROM AUTHOR]

Highlights • A cheaper way to validate the reactor-physics code SARAX for application in CFR is introduced. • The nuclear-data adjustment to extrapolate measurements to CFR is calculated and analyzed. • Different correlation coefficients between measurements are compared. Abstract The validation works have been implemented to a newly-developed code SARAX for China Fast Reactor (CFR) in this paper. Different with the conventional way to validate the code using the dedicated experimental data, a theoretical approach was proposed and implemented by using the existing similar experimental data. This theoretical approach is based on the technology of sensitivity/uncertainty analysis, similarity analysis and nuclear-data adjustment. In our previous works, detailed introduction towards sensitivity/uncertainty analysis and similarity analysis have been implemented to distinguish the existing experiments which are 'similar' to the CFR's criticality characteristics. This paper focus on the method to extrapolate the 'similar' experimental data to predict the best-estimate measurements of CFR with application of nuclear-data adjustment, providing reference values to validate the SARAX code. From the numerical results, it can be observed that through nuclear-data adjustment, the simulation results of the existing experiments can agree well with corresponding measurements, with the bias reduced notably to be within 25 pcm. Moreover, the nuclear-data adjustment can also improve the nuclear-data uncertainties notably, with the relative uncertainties of the reactor k eff due to nuclear data having been reduced from the value exceeding 1.0% to the values about 0.15%. [ABSTRACT FROM AUTHOR]

Highlights • The impact of four sampling approaches on evacuation simulations is investigated. • Stratified and the Inverse Stratified require the least number of simulation runs. • Halton sampling approach needs the greatest number of simulation runs. • Halton sampling generates the highest variance for the simulated total evacuation time. Abstract Simulating human behaviour in fire is often one of the main challenges in designing complex buildings, structures or sites for the life safety of occupants. In fact, evacuation simulations represent a fundamental input to assess fire safety performance using a risk analysis approach. The variability in evacuee behaviours (e.g. pre-evacuation delays and uncongested walking speed) can be probabilistically simulated in egress models using distribution functions. The application of probabilistic simulations requires the input distributions to be sampled. This paper describes a series of eight repeated trial evacuations that were carried out using a classroom-based scenario. The paper then investigates how four different sampling methods (namely Simple Random, Stratified, Inversed Stratified and Halton) affect the ability of a computational egress tool to reach convergence when determining the total time for occupants to leave the room. The analysis found that the Stratified and the Inverse Stratified sampling approaches require the least number of simulation runs to converge while the Halton sampling approach needs the greatest number of simulation runs. Moreover, the results indicate that the Halton sampling generates the highest variance for the simulated total evacuation time and thus is more effective at examining scenarios that utilise the extreme ends of the distribution functions. [ABSTRACT FROM AUTHOR]

Highlights • An approach for recovering absolute scale for Structure from Motion was proposed. • This approach creatively recovers absolute scale using a universal kinematic law. • The motion of the center of perspective of the camera is for the first time used. Abstract Reconstructions of objects (or scenes) using Structure from Motion (SfM) based on monocular camera or multiple uncalibrated cameras are only possible up to an unknown scale. Most of existing approaches for recovering absolute scale for SfM rely on additional constraints in absolute scale quantified by either metric data of the object (or scene) or motion data of the camera(s). This paper presented a novel approach for recovering absolute scale for SfM based on motion constraints defined by a relative free fall motion between the camera and the object. The proposed approach is strict because the adopted relative free fall motion is directly reconstructed by SfM and is therefore not complicated by the intrinsic problem that the motion of the camera recorded by external sensors cannot truly represent the motion of the center of perspective of the camera. Experiments of the proposed approach based on a widely used SfM-MVS pipeline had derived scale factors with relative errors smaller than 5%, yet returned camera motions that did not approximate with a reasonable degree of accuracy to what the law of free fall predicted. It is suggested that this deviation is owing to that SfM processes are not constrained by physical laws, and might be moderated by fusing kinematic constraints of free fall motion into bundle adjustment. In addition, uncertainties related to camera properties and experiment designs should also be reduced so that the proposed closed-form analytical solution for recovering absolute scale can work properly in practice. To our knowledge, this paper for the first time shows the potential of recovering absolute scale for geometric SfM reconstruction using a universal physical law. [ABSTRACT FROM AUTHOR]

Highlights • The paper surveys and compares clusterability tests. • New clusterability tests are proposed. • Type I error and power of clusterability methods are reported for simulated data. • Clusterablity tests are applied to well-known non-simulated data. • Provide guidelines to help users to select among clusterability tests. Abstract Clustering is an essential data mining tool that aims to discover inherent cluster structure in data. For most applications, applying clustering is only appropriate when cluster structure is present. As such, the study of clusterability, which evaluates whether data possesses such structure, is an integral part of cluster analysis. However, methods for evaluating clusterability vary radically, making it challenging to select a suitable measure. In this paper, we perform an extensive comparison of measures of clusterability and provide guidelines that clustering users can reference to select suitable measures for their applications. [ABSTRACT FROM AUTHOR]