Artículos de revistas sobre el tema "Distributed environment simulator"

Practical evaluation of the Unmanned Aerial Vehicle (UAV) network requires a lot of money to build experiment environments, which includes UAVs, network devices, flight controllers, and so on. To investigate the time-sensitivity of the multi-UAV network, the influence of the UAVs’ mobility should be precisely evaluated in the long term. Although there are some simulators for UAVs’ physical flight, there is no explicit scheme for simulating both the network environment and the flight environments simultaneously. In this paper, we propose a novel co-simulation scheme for the multiple UAVs network, which performs the flight simulation and the network simulation simultaneously. By considering the dependency between the flight status and networking situations of UAV, our work focuses on the consistency of simulation state through synchronization among simulation components. Furthermore, we extend our simulator to perform multiple scenarios by exploiting distributed manner. We verify our system with respect to the robustness of time management and propose some use cases which can be solely simulated by this.

Unmanned aerial vehicles (UAVs) have shown great potential in various applications such as surveillance, search and rescue. To perform safe and efficient navigation, it is vitally important for a UAV to evaluate the environment accurately and promptly. In this work, we present a simulation study for the estimation of foliage distribution as a UAV equipped with biosonar navigates through a forest. Based on a simulated forest environment, foliage echoes are generated by using a bat-inspired bisonar simulator. These biosonar echoes are then used to estimate the spatial distribution of both sparsely and densely distributed tree leaves. While a simple batch processing method is able to estimate sparsely distributed leaf locations well, a wavelet scattering technique coupled with a support vector machine (SVM) classifier is shown to be effective to estimate densely distributed leaves. Our approach is validated by using multiple setups of leaf distributions in the simulated forest environment. Ninety-seven percent accuracy is obtained while estimating thickly distributed foliage.

Abstract The evolution of simulators from proprietary hardware platforms to affordable commercial-off-the-shelf (COTS) platforms has gone on for the past 15 years and is now nearly complete. Nevertheless, past efforts to standardise simulator synthetic environments (SE) have only been partially successful and have engendered considerable aggravation for users in need of creating content that can be deployed to distributed full-mission simulators. This paper provides a detailed description of the SE generation pipeline and the reasoning that has modeled its evolution over the past few decades. The arrival of digital multi-spectral high-resolution satellite imagery and highly capable visual systems now requires orders of magnitude more storage and processing than equivalent databases just a few years ago. These factors are threatening the equilibrium of the SE pipeline and are becoming important elements affecting SE interoperability, portability and re-usability. Past design trade-offs and compromises, appropriate at the time, must now be re-examined along with all SE-related processes, starting from ingestion of raw source data right through to the processing by the simulator devices. Clearly, greater standardisation is needed within the simulation community and a comprehensive, open SE representation would palliate to the many challenges we now face. To this end, this paper provides a checklist of the characteristics for a future ‘ideal’ SE representation and evaluates four emerging synthetic environment initiatives against this extensive checklist.

The Air Force Institute of Technology Virtual Environments, 3-D Medical Imaging, and Computer Graphics Laboratory is investigating the 3-D computer graphics, user-interface design, networking protocol, and software architecture aspects of distributed virtual environments. In this paper we describe the research projects that are underway in the laboratory. These projects include the development of an aircraft simulator for a distributed virtual environment, projects for observing, analyzing, and understanding virtual environments, a space virtual environment, a project that incorporates “live” aircraft range data into a distributed virtual environment, a virtual environment application framework, and a project for use in a hospital emergency department. We also discuss the research equipment infrastructure in the laboratory, recent publications, and the educational services we provide.

Cyberattacks in the modern world are sophisticated and can be undetected in a dispersed setting. In a distributed setting, DoS and DDoS attacks cause resource unavailability. This has motivated the scientific community to suggest effective approaches in distributed contexts as a means of mitigating such attacks. Syn Flood is the most common sort of DDoS assault, up from 76% to 81% in Q2, according to Kaspersky’s Q3 report. Direct and indirect approaches are also available for launching DDoS attacks. While in a DDoS attack, controlled traffic is transmitted indirectly through zombies to reflectors to compromise the target host, in a direct attack, controlled traffic is sent directly to zombies in order to assault the victim host. Reflectors are uncompromised systems that only send replies in response to a request. To mitigate such assaults, traffic shaping and pushback methods are utilised. The SYN Flood Attack Detection and Mitigation Technique (SFaDMT) is an adaptive heuristic-based method we employ to identify DDoS SYN flood assaults. This study suggested an effective strategy to identify and resist the SYN assault. A decision support mechanism served as the foundation for the suggested (SFaDMT) approach. The suggested model was simulated, analysed, and compared to the most recent method using the OMNET simulator. The outcome demonstrates how the suggested fix improved detection.

We present a modular platform simulation environment to estimate the energy consumption and performance of distributed systems in a Systems-on-Chip context. We use the simulation environment to support the development of our high-level design methodologies. More in particular, we steer and verify the development of a task-level data transfer and storage methodology, the development of a task-level scheduling methodology and the development of an instruction memory management methodology. All of these methodologies are focussed on reducing the overall energy consumption of the complex dynamic system on a heterogeneous platform architecture. Compared to research in the academic and industrial context, our contribution is to integrate in a scalable way existing energy and performance simulators of the components of a heterogeneous multiprocessor SoC. Also a novel instruction memory hierarchy is included. The simulation environment consists of multiple processing nodes connected to a distributed memory hierarchy. To reduce the energy consumption of the system, both the processing nodes as well as the memory architecture can be varied: the processing voltage of each node can be tuned and the memory hierarchy can be fully customized. The integration of dynamic real-time applications on this platform is simplified by the availability of a multi-processor RTOS. The use of the simulator to develop our high-level design methodologies is illustrated on real-life multimedia applications.

The Internet’s rapid growth has spurred the development of new protocols and algorithms to meet changing operational requirements such as security, multicast transport, mobile networking, policy management, and quality of service support. Development and evaluation of these operational tools requires answering many design questions. This work proposes a computer network simulation program, devoted for wired LAN systems. The simulator would be able to work under Microsoft Windows NT platforms, also it has the potential to provide an emulation environment which should be suitable for testing protocols above the TCP layer under the Windows NT platform supported network layers, and offering scalability by running the simulator under distributed network system.

AbstractTo meet the challenges in software testing for automated vehicles, such as increasing system complexity and an infinite number of operating scenarios, new simulation methods must be developed. Closed-loop simulations for automated driving (AD) require highly complex simulation models for multiple controlled vehicles with their perception systems as well as their surrounding context. For the realization of such models, different simulation domains must be coupled with co-simulation. However, widely supported model integration standards such as functional mock-up interface (FMI) lack native support for distributed platforms, which is a key feature for AD due to the computational intensity and platform exclusivity of certain models. The newer FMI companion standard distributed co-simulation protocol (DCP) introduces platform coupling but must still be used in conjunction with AD co-simulations. As part of an assessment framework for AD, this paper presents a DCP compliant implementation of an interoperable interface between a 3D environment and vehicle simulator and a co-simulation platform. A universal Python wrapper is implemented and connected to the simulator to allow its control as a DCP slave. A C-code-based interface enables the co-simulation platform to act as a DCP master and to realize cross-platform data exchange and time synchronization of the environment simulation with other integrated models. A model-in-the-loop use case is performed with the traffic simulator CARLA running on a Linux machine connected to the co-simulation master xMOD on a Windows computer via DCP. Several virtual vehicles are successfully controlled by cooperative adaptive cruise controllers executed outside of CARLA. The standard compliance of the implementation is verified by exemplary connection to prototypic DCP solutions from 3rd party vendors. This exemplary application demonstrates the benefits of DCP compliant tool coupling for AD simulation with increased tool interoperability, reuse potential, and performance.

The performance of airplane in commercial airline environment is determined by, and therefore an indicator of performance measure of, the thermodynamic properties of airplane. The aim of this study was to establish the use of simulators to determine aircraft accident for a flight of airplanes and evaluate the potential of new airspace structure and airport’s runway. This indicates that there is a possibility of obtaining airplane performance from analysis and verification simulating airplane. As compared with AIRBUS Full Flight Simulator, a multiple aircrafts flight simulator that grouping aircrafts simultaneously take off and land was presented, which is basis on a parallel distributed computing in Open Grid Computing Environment (OGCE), and service oriented architecture (SOA) of software in multiple aircraft simulator, the performance of collaborative flight of multiple aircrafts is evaluated.

In today’s environment, pervasive computing plays important role to perform data transmission between IoT objects in distributed environment which communicate, each other directly without any centralized object. Security is very challenging task in pervasive computing where simulation environment is distributed. In this paper, an attempt has been made to resolve this kind of issues and a secure trust based signals transmission in distributed environment of pervasive computing mechanism has been proposed. In this trust value of each IoT object is calculated on the basis of their context information and these objects have been distinguished on the basis of this trust value that either the object is trusted or not. Later, propose a mechanism to enhance utilization of energy of resources used in smart office environment and this has been implemented in ONE (Opportunistic Network Environment) simulator.

Automated driving technologies offer the opportunity to substantially reduce the number of road accidents and fatalities. This requires the development of systems that can handle traffic scenarios more reliable than the human driver. The extreme number of traffic scenarios, though, causes enormous challenges in testing and proving the correct system functioning. Due to its efficiency and reproducibility, the test procedure will involve environment simulations to which the system under test is exposed. A combination of traffic, driving and Vulnerable Road User (VRU) simulation is therefore required for a holistic environment simulation. Since these simulators have different requirements and support various formats, a concept for integrated spatio-semantic road space modeling is proposed in this paper. For this purpose, the established standard OpenDRIVE, which describes road networks with their topology for submicroscopic driving simulation and HD maps, is combined with the internationally used semantic 3D city model standard CityGML. Both standards complement each other, and their combination opens the potentials of both application domains—automotive and 3D GIS. As a result, existing HD maps can now be used by model processing tools, enabling their transformation to the target formats of the respective simulators. Based on this, we demonstrate a distributed environment simulation with the submicroscopic driving simulator Virtual Test Drive and the pedestrian simulator MomenTUM at a sensitive crossing in the city of Ingolstadt. Both simulators are coupled at runtime and the architecture supports the integration of automated driving functions.

We present a simulation environment called SPIKELAB which incorporates a simulator that is able to simulate large networks of spiking neurons using a distributed event driven simulation. Contrary to a time driven simulation, which is usually used to simulate spiking neural networks, our simulation needs less computational resources because of the low average activity of typical networks. The paper addresses the speed up using an event driven versus a time driven simulation and how large networks can be simulated by a distribution of the simulation using already available computing resources. It also presents a solution for the integration of digital or analogue neuromorphic circuits into the simulation process.

Abstract Air-to-ground strike has become one of main forms of modern warfare, and the guided bomb release is an important and key part of the attack. The guided bomb release planning aims to accomplish a precise target hit in enemy’s region while guarantee the pilot’s safety. We propose a robust Monte Carlo method by taking error perturbations into consideration, comparing to the traditional sequential quadratic programming method under extreme conditions. At the same time using a distributed virtual physics environment we can obtain much more detailed realism relative to the conventional simulator running on a single machine. The experimental results verify that Monte Carlo methods can improve hit probability and weapon efficiency significantly. Furthermore, the 3D visualised environment plays a very important role in training pilots, so this simulator will decrease the cost and time requirements of physical experiment that are not always compatible with strict military task.

This paper deals with the verification of a multi-agent system simulator. Agents in the simulator are based on the Mobile Agent Network (MAN) formal model. It describes a shared plan representing a process which allows team formation according to task complexity and the characteristics of the distributed environment where these tasks should be performed. In order to verify the simulation results, we compared them with performance characteristics of a real multi-agent system, called the Multi-Agent Remote Maintenance Shell (MA–RMS). MA–RMS is organized as a team-oriented knowledge based system responsible for distributed software management. The results are compared and analyzed for various testing scenarios which differ with respect to network bandwidth as well as task and network complexity.

Summary The design process of carbonate matrix acidizing treatments requires coring and conducting linear, radial coreflood experiments. With the current environment revolving around cutting costs, it has become increasingly important to accurately design cost-effective acidizing treatments. This work aims to introduce a novel approach to predicting the performance of acid treatments in the field using log data only. A radial reactive flow simulator, using porosity distributed from logs, is used to provide accurate predictions without the need for experiments. Coreflood acidizing experiments at 150 and 200°F with two acid concentrations were studied. A reactive flow simulator was built using porosity distribution derived from computed-tomography (CT) scans and tuned to match experimental data. A new radial simulation model of 3.25-ft radius was used to study acid propagation under field conditions. For accurate predictions, porosity was distributed using values derived from cores’ CT scans. Simulation results were compared with traditional 1D models. Different porosity distributions, including gamma distributions, were used in the radial model. The reactive flow simulator was able to accurately capture wormhole propagation inside the linear core. A greater than 90% match between the experimental and the simulated acid pore volume (PV) to breakthrough (PVBT) was obtained using two acid concentrations’ different temperatures. The simulation results from the radial field-scale model show that the optimal velocity can be higher or lower than those predicted from laboratory experiments. Accordingly, caution must be taken when linear coreflood data are used to predict acid propagation in the field. The simulations showed that traditional upscaling models overpredict acid volumes; the predicted volumes are double at moderate to high injection rates. Models using statistically distributed porosity can provide accurate acid-propagation predictions, with a relative percentage error of less than 25% at extremely high injection rates. This work introduces an accurate model using porosity directly from logs to predict acid performance while avoiding expensive designs. The simulation results reveal that traditional designs overpredict acid volumes required for field treatments. The statistically distributed porosity can be used as a substitute for CT-scan-derived porosity with a low effect on model predictability. The reactive flow simulator can accurately match experimental data.

Abstract: Fog computing is one of the new computing structures which takes the Cloud to the verge of the network. The structure is formulated for applications that need low latency. Fog Computing has been projected to improve the disadvantages of Cloud Computing. The system is confronted with the variability of dynamic resources that are heterogeneous and distributed. Hence, efficient scheduling and resource allocation are necessary to maximize the use of these resources and the satisfaction of users. In this paper, a resource-aware scheduler RACE (Resource Aware Cost-Efficient Scheduler) is proposed to distribute the incoming application modules to Fog devices that maximize resource utilization at the Fog layer, reduces the monetary cost of using Cloud resources with minimum execution time of applications and minimum bandwidth usage. This RACE comprises of two algorithms. The Module Scheduler in RACE categorizes the incoming application modules according to their computation and bandwidth requirements which are then placed by Compare Module. Comprehensive experimental results obtained from the simulation by using ifogsim simulator show that our approach performs better in most of the cases as compared to the Traditional Cloud placement and the baseline algorithm.

AbstractThis paper describes four agribusiness simulators which can be processed on a microcomputer for use in undergraduate and extension teaching. The simulators model the environment in which supermarket chains, farm supply centers, and cooperative and proprietary grain elevators compete for business. Instruction manuals, user's manuals, and a diskette are distributed for each simulator. Each diskette contains programs to enter and edit team decisions, to process decisions and print reports, and to create graphs of team performance. The simulators can be used to teach financial management concepts and techniques, as well as economic principles.

Distributed average consensus represents the amount of computing of inputs held by multiple agents that communicate through peer-to-peer networks. Collaboration among operators is essential for any distributed standard consensus protocol as every specialist needs to contribute to different operators, typically the adjacent (neighbouring) operators. Internet-of-Things (IoT) implementation is challenging because of its heterogeneous, massively distributed nature. The challenges of this challenge can be addressed with blockchain-based platforms and technologies. Testing and evaluation platforms are required for Blockchain deployments in IoT. A realistic and configurable network environment is presented in this paper to evaluate consensus algorithms. Many blockchainevaluation platforms do not provide a configurable and realistic network environment or are tied to a specific consensus protocol. With our simulator, practitioners can evaluate how consensus algorithms affect network events in congested or contested scenarios to determine the best consensus algorithm. It is proposed to achieve this task by generalizing consensus methods. The Blockchain simulator employs Discrete event network simulations for increased fidelity and scalability. In addition to evaluating the time, state block rate (%), estimation error, average throughput, and simulation time, we evaluate the performance of the proposed techniques based on the number of peer nodes. A comparison of the average transaction delivery rate with a traditional protocol is shown. The proposed protocol has a higher throughput average than the traditional one.

This paper examines the problem of distributed coverage of an initially unknown environment using a multi-robot system. Specifically, focus is on a coverage technique for coordinating teams of multiple mobile robots that are deployed and maintained in a certain formation while covering the environment. The technique is analyzed theoretically and experimentally to verify its operation and performance within the Webots robot simulator, as well as on physical robots. Experimental results show that the described coverage technique with robot teams moving in formation can perform comparably with a technique where the robots move individually while covering the environment. The authors also quantify the effect of various parameters of the system, such as the size of the robot teams, the presence of localization, and wheel slip noise, as well as environment related features like the size of the environment and the presence of obstacles and walls on the performance of the area coverage operation.

Undergraduate robotics students often find it difficult to design and validate control algorithms for teams of mobile robots. This is mainly due to two reasons. First, very rarely, educational laboratories are equipped with large teams of robots, which are usually expensive, bulky, and difficult to manage and maintain. Second, robotics simulators often require students to spend much time to learn their use and functionalities. For this purpose, a simulator of multiagent mobile robots namedMARShas been developed within the Matlab environment, with the aim of helping students to simulate a wide variety of control algorithms in an easy way and without spending time for understanding a new language. Through this facility, the user is able to simulate multirobot teams performing different tasks, from cooperative to competitive ones, by using both centralized and distributed controllers. Virtual sensors are provided to simulate real devices. A graphical user interface allows students to monitor the robots behaviour through an online animation.

Proton Exchange Membrane Fuel Cell (PEMFC) has being widely applied in electric vehicle and distributed generation for its low corrosion, low-temperature operation and environment friendship. It should be concerned over the control and maintenance of its auxiliary equipments, placement site, restoring of hydrogen and other things when physical PEMFC is used. However, PEMFC’s volt-ampere (V-I) external characteristics draw our more attention rather than its ontology or peripheral devices control which keeps PEMFC working properly in many appliance studies. So, there is another solution to introduce power electronic technique to construct a FC power electronic simulator which simulates FC’s external characteristic including static and dynamic states and keeps away those troubles mentioned above. A buck converter is adopted to construct the FC simulator. The test DC current source load is acquired by a buck converter which main circuit is similar to the FC simulator. The experiments show the FC simulator has done a good job to simulator FC’s volt-ampere external characteristic and it is cost saved.

SUMMARYIn this paper, we present a novel algorithm for exploring an unknown environment using a team of mobile robots. The suggested algorithm is a grid-based search method that utilizes a triangular pattern which covers an area so that exploring the whole area is guaranteed. The proposed algorithm consists of two stages. In the first stage, all the members of the team make a common triangular grid of which they are located on the vertices. In the second stage, they start exploring the area by moving between vertices of the grid. Furthermore, it is assumed that the communication range of the robots is limited, and the algorithm is based on the information of the nearest neighbours of the robots. Moreover, we apply a new mapping method employed by robots during the search operation. A mathematically rigorous proof of convergence with probability 1 of the algorithm is given. Moreover, our algorithm is implemented and simulated using a simulator of the real robots and environment and also tested via experiments with Adept Pioneer 3DX wheeled mobile robots.

Abstract This paper presents a software/hardware bundle for studying, training and research related to IEEE 1149.1 Boundary Scan (BS) standard. The presented package includes a software environment Trainer 1149 that is capable to graphically visualize BS facilities and perform fine-grain simulation of BS test process. Trainer 1149 provides a cozy graphical design and simulation environment of BS-enabled chips and non-BS clusters. It provides the user with a full flexibility in working with any type of BS structures by supporting standard formats such as Boundary Scan Description Language and SVF (for defining test patterns). A special fault simulation mode allows injecting various types of interconnection faults to simulate their impact and inspect them using interactive tools. Trainer 1149 is the main component of a recent goJTAG initiative that aims at bringing JTAG tools closer to the user for both learning and experimental work purposes. The software part is implemented in multi-platform Java environment and distributed as an open-source freeware. Using a convenient low-cost USB-JTAG controller, one can also test real defects in real hardware. Such combination of features is unique for a public domain BS package.

In this paper, a miniaturization method is proposed for developing micro distributed generation for a micro smart grid simulator. The micro smart grid simulator is a fault simulator that was built to test and verify the new operation control algorithms for smart grids in the laboratory and has a size downscaled to one-thousandth of that of an actual smart grid. The micro distributed generation was designed in a multi-layered structure (dimension: 13 × 20 cm2), in which each function is implemented in several layers, to satisfy the size requirements. Next, the grid synchronization and PQ control algorithms required for the distributed generation were developed. A three-phase 19 V power system was built, and a 19 V–7.5 W three-phase micro distributed generation was realized through experimental verification. In addition, by verifying the effectiveness through grid synchronization and 7.5 W PQ control experiments, it was confirmed that the micro distributed generation based on the proposed miniaturization method can be implemented in a micro smart grid simulator.

To date, discrete event stochastic simulations of large scale biological reaction systems are extremely compute-intensive and time-consuming. Besides, it has been widely accepted that spatial factor plays a critical role in the dynamics of most biological reaction systems. The NSM (the Next Sub-Volume Method), a spatial variation of the Gillespie’s stochastic simulation algorithm (SSA), has been proposed for spatially stochastic simulation of those systems. While being able to explore high degree of parallelism in systems, NSM is inherently sequential, which still suffers from the problem of low simulation speed. Fine-grained parallel execution is an elegant way to speed up sequential simulations. Thus, based on the discrete event simulation framework JAMES II, we design and implement a PDES (Parallel Discrete Event Simulation) TW (time warp) simulator to enable the fine-grained parallel execution of spatial stochastic simulations of biological reaction systems using the ANSM (the Abstract NSM), a parallel variation of the NSM. The simulation results of classical Lotka-Volterra biological reaction system show that our time warp simulator obtains remarkable parallel speed-up against sequential execution of the NSM.I.IntroductionThe goal of Systems biology is to obtain system-level investigations of the structure and behavior of biological reaction systems by integrating biology with system theory, mathematics and computer science [1][3], since the isolated knowledge of parts can not explain the dynamics of a whole system. As the complement of “wet-lab” experiments, stochastic simulation, being called the “dry-computational” experiment, plays a more and more important role in computing systems biology [2]. Among many methods explored in systems biology, discrete event stochastic simulation is of greatly importance [4][5][6], since a great number of researches have present that stochasticity or “noise” have a crucial effect on the dynamics of small population biological reaction systems [4][7]. Furthermore, recent research shows that the stochasticity is not only important in biological reaction systems with small population but also in some moderate/large population systems [7].To date, Gillespie’s SSA [8] is widely considered to be the most accurate way to capture the dynamics of biological reaction systems instead of traditional mathematical method [5][9]. However, SSA-based stochastic simulation is confronted with two main challenges: Firstly, this type of simulation is extremely time-consuming, since when the types of species and the number of reactions in the biological system are large, SSA requires a huge amount of steps to sample these reactions; Secondly, the assumption that the systems are spatially homogeneous or well-stirred is hardly met in most real biological systems and spatial factors play a key role in the behaviors of most real biological systems [19][20][21][22][23][24]. The next sub-volume method (NSM) [18], presents us an elegant way to access the special problem via domain partition. To our disappointment, sequential stochastic simulation with the NSM is still very time-consuming, and additionally introduced diffusion among neighbor sub-volumes makes things worse. Whereas, the NSM explores a very high degree of parallelism among sub-volumes, and parallelization has been widely accepted as the most meaningful way to tackle the performance bottleneck of sequential simulations [26][27]. Thus, adapting parallel discrete event simulation (PDES) techniques to discrete event stochastic simulation would be particularly promising. Although there are a few attempts have been conducted [29][30][31], research in this filed is still in its infancy and many issues are in need of further discussion. The next section of the paper presents the background and related work in this domain. In section III, we give the details of design and implementation of model interfaces of LP paradigm and the time warp simulator based on the discrete event simulation framework JAMES II; the benchmark model and experiment results are shown in Section IV; in the last section, we conclude the paper with some future work.II. Background and Related WorkA. Parallel Discrete Event Simulation (PDES)The notion Logical Process (LP) is introduced to PDES as the abstract of the physical process [26], where a system consisting of many physical processes is usually modeled by a set of LP. LP is regarded as the smallest unit that can be executed in PDES and each LP holds a sub-partition of the whole system’s state variables as its private ones. When a LP processes an event, it can only modify the state variables of its own. If one LP needs to modify one of its neighbors’ state variables, it has to schedule an event to the target neighbor. That is to say event message exchanging is the only way that LPs interact with each other. Because of the data dependences or interactions among LPs, synchronization protocols have to be introduced to PDES to guarantee the so-called local causality constraint (LCC) [26]. By now, there are a larger number of synchronization algorithms have been proposed, e.g. the null-message [26], the time warp (TW) [32], breath time warp (BTW) [33] and etc. According to whether can events of LPs be processed optimistically, they are generally divided into two types: conservative algorithms and optimistic algorithms. However, Dematté and Mazza have theoretically pointed out the disadvantages of pure conservative parallel simulation for biochemical reaction systems [31]. B. NSM and ANSM The NSM is a spatial variation of Gillespie’ SSA, which integrates the direct method (DM) [8] with the next reaction method (NRM) [25]. The NSM presents us a pretty good way to tackle the aspect of space in biological systems by partitioning a spatially inhomogeneous system into many much more smaller “homogeneous” ones, which can be simulated by SSA separately. However, the NSM is inherently combined with the sequential semantics, and all sub-volumes share one common data structure for events or messages. Thus, directly parallelization of the NSM may be confronted with the so-called boundary problem and high costs of synchronously accessing the common data structure [29]. In order to obtain higher efficiency of parallel simulation, parallelization of NSM has to firstly free the NSM from the sequential semantics and secondly partition the shared data structure into many “parallel” ones. One of these is the abstract next sub-volume method (ANSM) [30]. In the ANSM, each sub-volume is modeled by a logical process (LP) based on the LP paradigm of PDES, where each LP held its own event queue and state variables (see Fig. 1). In addition, the so-called retraction mechanism was introduced in the ANSM too (see algorithm 1). Besides, based on the ANSM, Wang etc. [30] have experimentally tested the performance of several PDES algorithms in the platform called YH-SUPE [27]. However, their platform is designed for general simulation applications, thus it would sacrifice some performance for being not able to take into account the characteristics of biological reaction systems. Using the similar ideas of the ANSM, Dematté and Mazza have designed and realized an optimistic simulator. However, they processed events in time-stepped manner, which would lose a specific degree of precisions compared with the discrete event manner, and it is very hard to transfer a time-stepped simulation to a discrete event one. In addition, Jeschke etc.[29] have designed and implemented a dynamic time-window simulator to execution the NSM in parallel on the grid computing environment, however, they paid main attention on the analysis of communication costs and determining a better size of the time-window.Fig. 1: the variations from SSA to NSM and from NSM to ANSMC. JAMES II JAMES II is an open source discrete event simulation experiment framework developed by the University of Rostock in Germany. It focuses on high flexibility and scalability [11][13]. Based on the plug-in scheme [12], each function of JAMES II is defined as a specific plug-in type, and all plug-in types and plug-ins are declared in XML-files [13]. Combined with the factory method pattern JAMES II innovatively split up the model and simulator, which makes JAMES II is very flexible to add and reuse both of models and simulators. In addition, JAMES II supports various types of modelling formalisms, e.g. cellular automata, discrete event system specification (DEVS), SpacePi, StochasticPi and etc.[14]. Besides, a well-defined simulator selection mechanism is designed and developed in JAMES II, which can not only automatically choose the proper simulators according to the modeling formalism but also pick out a specific simulator from a serious of simulators supporting the same modeling formalism according to the user settings [15].III. The Model Interface and SimulatorAs we have mentioned in section II (part C), model and simulator are split up into two separate parts. Thus, in this section, we introduce the designation and implementation of model interface of LP paradigm and more importantly the time warp simulator.A. The Mod Interface of LP ParadigmJAMES II provides abstract model interfaces for different modeling formalism, based on which Wang etc. have designed and implemented model interface of LP paradigm[16]. However, this interface is not scalable well for parallel and distributed simulation of larger scale systems. In our implementation, we accommodate the interface to the situation of parallel and distributed situations. Firstly, the neighbor LP’s reference is replaced by its name in LP’s neighbor queue, because it is improper even dangerous that a local LP hold the references of other LPs in remote memory space. In addition, (pseudo-)random number plays a crucial role to obtain valid and meaningful results in stochastic simulations. However, it is still a very challenge work to find a good random number generator (RNG) [34]. Thus, in order to focus on our problems, we introduce one of the uniform RNGs of JAMES II to this model interface, where each LP holds a private RNG so that random number streams of different LPs can be independent stochastically. B. The Time Warp SimulatorBased on the simulator interface provided by JAMES II, we design and implement the time warp simulator, which contains the (master-)simulator, (LP-)simulator. The simulator works strictly as master/worker(s) paradigm for fine-grained parallel and distributed stochastic simulations. Communication costs are crucial to the performance of a fine-grained parallel and distributed simulation. Based on the Java remote method invocation (RMI) mechanism, P2P (peer-to-peer) communication is implemented among all (master-and LP-)simulators, where a simulator holds all the proxies of targeted ones that work on remote workers. One of the advantages of this communication approach is that PDES codes can be transferred to various hardwire environment, such as Clusters, Grids and distributed computing environment, with only a little modification; The other is that RMI mechanism is easy to realized and independent to any other non-Java libraries. Since the straggler event problem, states have to be saved to rollback events that are pre-processed optimistically. Each time being modified, the state is cloned to a queue by Java clone mechanism. Problem of this copy state saving approach is that it would cause loads of memory space. However, the problem can be made up by a condign GVT calculating mechanism. GVT reduction scheme also has a significant impact on the performance of parallel simulators, since it marks the highest time boundary of events that can be committed so that memories of fossils (processed events and states) less than GVT can be reallocated. GVT calculating is a very knotty for the notorious simultaneous reporting problem and transient messages problem. According to our problem, another GVT algorithm, called Twice Notification (TN-GVT) (see algorithm 2), is contributed to this already rich repository instead of implementing one of GVT algorithms in reference [26] and [28].This algorithm looks like the synchronous algorithm described in reference [26] (pp. 114), however, they are essentially different from each other. This algorithm has never stopped the simulators from processing events when GVT reduction, while algorithm in reference [26] blocks all simulators for GVT calculating. As for the transient message problem, it can be neglect in our implementation, because RMI based remote communication approach is synchronized, that means a simulator will not go on its processing until the remote the massage get to its destination. And because of this, the high-costs message acknowledgement, prevalent over many classical asynchronous GVT algorithms, is not needed anymore too, which should be constructive to the whole performance of the time warp simulator.IV. Benchmark Model and Experiment ResultsA. The Lotka-Volterra Predator-prey SystemIn our experiment, the spatial version of Lotka-Volterra predator-prey system is introduced as the benchmark model (see Fig. 2). We choose the system for two considerations: 1) this system is a classical experimental model that has been used in many related researches [8][30][31], so it is credible and the simulation results are comparable; 2) it is simple but helpful enough to test the issues we are interested in. The space of predator-prey System is partitioned into a2D NXNgrid, whereNdenotes the edge size of the grid. Initially the population of the Grass, Preys and Predators are set to 1000 in each single sub-volume (LP). In Fig. 2,r1,r2,r3stand for the reaction constants of the reaction 1, 2 and 3 respectively. We usedGrass,dPreyanddPredatorto stand for the diffusion rate of Grass, Prey and Predator separately. Being similar to reference [8], we also take the assumption that the population of the grass remains stable, and thusdGrassis set to zero.R1:Grass + Prey ->2Prey(1)R2:Predator +Prey -> 2Predator(2)R3:Predator -> NULL(3)r1=0.01; r2=0.01; r3=10(4)dGrass=0.0;dPrey=2.5;dPredato=5.0(5)Fig. 2: predator-prey systemB. Experiment ResultsThe simulation runs have been executed on a Linux Cluster with 40 computing nodes. Each computing node is equipped with two 64bit 2.53 GHz Intel Xeon QuadCore Processors with 24GB RAM, and nodes are interconnected with Gigabit Ethernet connection. The operating system is Kylin Server 3.5, with kernel 2.6.18. Experiments have been conducted on the benchmark model of different size of mode to investigate the execution time and speedup of the time warp simulator. As shown in Fig. 3, the execution time of simulation on single processor with 8 cores is compared. The result shows that it will take more wall clock time to simulate much larger scale systems for the same simulation time. This testifies the fact that larger scale systems will leads to more events in the same time interval. More importantly, the blue line shows that the sequential simulation performance declines very fast when the mode scale becomes large. The bottleneck of sequential simulator is due to the costs of accessing a long event queue to choose the next events. Besides, from the comparison between group 1 and group 2 in this experiment, we could also conclude that high diffusion rate increased the simulation time greatly both in sequential and parallel simulations. This is because LP paradigm has to split diffusion into two processes (diffusion (in) and diffusion (out) event) for two interactive LPs involved in diffusion and high diffusion rate will lead to high proportional of diffusion to reaction. In the second step shown in Fig. 4, the relationship between the speedups from time warp of two different model sizes and the number of work cores involved are demonstrated. The speedup is calculated against the sequential execution of the spatial reaction-diffusion systems model with the same model size and parameters using NSM.Fig. 4 shows the comparison of speedup of time warp on a64X64grid and a100X100grid. In the case of a64X64grid, under the condition that only one node is used, the lowest speedup (a little bigger than 1) is achieved when two cores involved, and the highest speedup (about 6) is achieved when 8 cores involved. The influence of the number of cores used in parallel simulation is investigated. In most cases, large number of cores could bring in considerable improvements in the performance of parallel simulation. Also, compared with the two results in Fig. 4, the simulation of larger model achieves better speedup. Combined with time tests (Fig. 3), we find that sequential simulator’s performance declines sharply when the model scale becomes very large, which makes the time warp simulator get better speed-up correspondingly.Fig. 3: Execution time (wall clock time) of Seq. and time warp with respect to different model sizes (N=32, 64, 100, and 128) and model parameters based on single computing node with 8 cores. Results of the test are grouped by the diffusion rates (Group 1: Sequential 1 and Time Warp 1. dPrey=2.5, dPredator=5.0; Group 2: dPrey=0.25, dPredator=0.5, Sequential 2 and Time Warp 2).Fig. 4: Speedup of time warp with respect to the number of work cores and the model size (N=64 and 100). Work cores are chose from one computing node. Diffusion rates are dPrey=2.5, dPredator=5.0 and dGrass=0.0.V. Conclusion and Future WorkIn this paper, a time warp simulator based on the discrete event simulation framework JAMES II is designed and implemented for fine-grained parallel and distributed discrete event spatial stochastic simulation of biological reaction systems. Several challenges have been overcome, such as state saving, roll back and especially GVT reduction in parallel execution of simulations. The Lotka-Volterra Predator-Prey system is chosen as the benchmark model to test the performance of our time warp simulator and the best experiment results show that it can obtain about 6 times of speed-up against the sequential simulation. The domain this paper concerns with is in the infancy, many interesting issues are worthy of further investigated, e.g. there are many excellent PDES optimistic synchronization algorithms (e.g. the BTW) as well. Next step, we would like to fill some of them into JAMES II. 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Abstract Training in simulator has been used in maritime domain for years due to its cost-effective nature. Different scenarios with varied visibility, traffic density, weather conditions, etc. could be easily set up in the simulators. However, the existing build-in training and assessment package in the simulators is rigid as it does not take into consideration the change in traffic and navigational environment. Human experts are always involved to observe and assess the performance of trainees. An objective and intelligent training and assessment package is proposed to assist the experts in training to ensure objectivity and consistency. To identify the gaps and determine the relevance and the adequacy of the existing build-in assessment in the simulator, online survey has been distributed to the shipping companies and associations. The survey has gathered inputs on the actual shipboard practices when the seafarers are navigating in Singapore waters. This includes different types of vessels, vessel sizes, and external environment conditions such as visibility. The outcome of this analysis is used to form the baseline of a common practice at sea and used in the training and assessment package, which provides consistency in setting the critical training parameters. The training and assessment package reads the data from an advanced navigation research simulator and is able to sense changes and update itself in accordance with user-defined environment. Several assessment modules such as CPA under different traffic density and visibility, minimum distance from other vessels, rate of turn at different speed and loading conditions, will be covered by this training and assessment package.

Cloud computing is an emerging concept that makes better use of a large number of distributed resources. The most significant issue that affects the cloud computing environment is resource provisioning. Better performance in the shortest amount of time is an important goal in resource provisioning. Create the best solution for dynamically provisioning resources in the shortest time possible. This paper aims to perform resource provisioning with an optimal performance solution in the shortest time. Hybridization of two Meta-heuristics techniques, such as HSMOSA (Hybrid Spider Monkey Optimization with Simulated Annealing), is proposed in resource provisioning for cloud environment. Finds the global and local value using Spider Monkey Optimization's (SMO) social behavior and then utilizes Simulated Annealing (SA) to search around the global value in each iteration. As a result, the proposed approach aids in enhancing their chances of improving their position. The CloudSimPlus Simulator is used to test the proposed approach. The fitness value, execution time, throughput, mean, and standard deviation of the proposed method were calculated over various tasks and execution iterations. These performance metrics are compared with the PSO-SA algorithm. Simulation results validate the better working of the proposed HSMOSA algorithm with minimum time compared to the PSO-SA algorithm.

<p>Metaverse is an immersive, three-dimensional, virtual and online multi-user environment that allows people to communicate with each other socially and economically, regardless of location, using computing tools as personalized agents and simulations. In order to build the system, we define the guide as a free distributed application integration product, Spanish, IP voice system in metaverse, and integrated LMS (learning management system). The main tools to support this work are: 3D metaverse second life simulator, Moodle LMS, object-oriented dynamic link interface simulation, sloodle. Although the best example of metacosmic second life is an integrated world that can be accessed online. Academic experience is a master’s degree in Ibero American virtual environment management education from the University of Granada. It ended in the first quarter of 2010. It was developed in the temporary place of second life and carried out some tests and data collection. The Ibero American network ecaeva (digital visual communication strategy driven by virtual flow in the Latin American Caribbean European Union academic free trade area) promotes video conference experiments and meta poetry teaching. Epistemological strategies are case studies.</p>

<p>Metaverse is an immersive, three-dimensional, virtual and online multi-user environment that allows people to communicate with each other socially and economically, regardless of location, using computing tools as personalized agents and simulations. In order to build the system, we define the guide as a free distributed application integration product, Spanish, IP voice system in metaverse, and integrated LMS (learning management system). The main tools to support this work are: 3D metaverse second life simulator, Moodle LMS, object-oriented dynamic link interface simulation, sloodle. Although the best example of metacosmic second life is an integrated world that can be accessed online. Academic experience is a master’s degree in Ibero American virtual environment management education from the University of Granada. It ended in the first quarter of 2010. It was developed in the temporary place of second life and carried out some tests and data collection. The Ibero American network ecaeva (digital visual communication strategy driven by virtual flow in the Latin American Caribbean European Union academic free trade area) promotes video conference experiments and meta poetry teaching. Epistemological strategies are case studies.</p>

Abstract This paper deals with the problem of the collaborative mapping of unknown indoor environments by a homogeneous mobile robot team. For this aim, a distributed multi-agent coordination approach is proposed for the mapping process to offer a global view of the entire environment. First, the scheme starts by assigning the most suitable robots to the different zones of the environment to be mapped based on a bidding strategy. Then, while a Robot agent of the group explores its local surroundings and collects information about its neighborhood, it sends mapping data to the Human/Machine Interface agent to integrate them into a single global map. Furthermore, a geometric map representation and an algorithm based on obstacles and environment limits detection are used to provide an explicitly geometric representation of the workspace. For validation purposes, Player/Stage simulator is used to show the effectiveness of the proposed distributed approach and algorithms without needing a real multi-robot system and environment. Finally, various scenarios have been carried out and results are compared in terms of (i) required mapping time, (ii) accuracy of the global generated map, and (iii) number of exchanged messages between the agents.

Organisms evolve to increase their fitness, a process that may be described as climbing the fitness landscape. However, the fitness landscape of an individual site, i.e., the vector of fitness values corresponding to different variants at this site, can itself change with time due to changes in the environment or substitutions at other epistatically interacting sites. While there exist a number of simulators for modeling different aspects of molecular evolution, very few can accommodate changing landscapes. We present SELVa, the Simulator of Evolution with Landscape Variation, aimed at modeling the substitution process under a changing single-position fitness landscape in a set of evolving lineages that form a phylogeny of arbitrary shape. Written in Java and distributed as an executable jar file, SELVa provides a flexible framework that allows the user to choose from a number of implemented rules governing landscape change.

Robots in assisted living (RAL) are an alternative to support families and professional caregivers with a wide range of possibilities to take care of elderly people. Navigation of mobile robots is a challenging problem due to the uncertainty and dynamics of environments found in the context of places for elderly. To accomplish this goal, the navigation system tries to replicate such a complicated process inspired on the perception and judgment of human beings. In this work, we propose a novel nature-inspired control system for mobile RAL navigation using an artificial organic controller enhanced with vision-based strategies such as Hermite optical flow (OF) and convolutional neural networks (CNNs). Particularly, the Hermite OF is employed for obstacle motion detection while CNNs are occupied for obstacle distance estimation. We train the CNN using OF visual features guided by ultrasonic sensor-based measures in a 3D scenario. Our application is oriented to avoid mobile and fixed obstacles using a monocular camera in a simulated environment. For the experiments, we use the robot simulator V-REP, which is an integrated development environment into a distributed control architecture. Security and smoothness metrics as well as quantitative evaluation are computed and analyzed. Results showed that the proposed method works successfully in simulation conditions.

Boom-type roadheaders are commonly used for excavation of roadways in underground mines, tunnels, and other architectural structures using trenchless techniques, as well as sinking shafts and occasionally excavating the harder soil and softer formations in cut and cover construction. The main research and development of these machines is to offer solutions for automatic control. This refers to automation or robotization of the operation, and raises the possibility of their eventual unmanned operation. This article presents a roadheader research simulator which implements experimentally verified mathematical models describing the dynamics of a roadheader in operation and the rock cutting process. Due to very high computational requirements, a distributed system comprising several workstations connected via TCP/IP was used. Both the visualization of the roadheader in the heading face of the excavation and the graphic simulation of the course of the rock-cutting process were carried out using the Autodesk Inventor Professional 2022 graphics engine. It provided the simulator with a virtual scene environment and enabled the control of the roadheader model’s movement during the simulated cutting process, including the generation of breakout graphics in the heading face while drilling a roadway or tunnel. The presented roadheader simulator enables the determination of various time characteristics, for example, dynamic loads, power demand, efficiency, energy consumption, and others. It is still under development.

In multi-agent systems, the Dynamic Distributed Constraint Optimisation Problem (D-DCOP) framework is pivotal, allowing for the decomposition of global objectives into agent constraints. Proactive agent behaviour is crucial in such systems, enabling agents to anticipate future changes and adapt accordingly. Existing approaches, like Proactive Dynamic DCOP (PD-DCOP) algorithms, often necessitate a predefined environment model. We address the problem of enabling proactive agent behaviour in D-DCOPs where the dynamics model of the environment is unknown. Specifically, we propose an approach where agents learn local autoregressive models from observations, predicting future states to inform decision-making. To achieve this, we present a temporal experience-sharing message-passing algorithm that leverages dynamic agent connections and a distance metric to collate training data. Our approach outperformed baseline methods in a search-and-extinguish task using the RoboCup Rescue Simulator, achieving better total building damage. The experimental results align with prior work on the significance of decision-switching costs and demonstrate improved performance when the switching cost is combined with a learned model.

Connected vehicles are more vulnerable to attacks than wired networks since they involve rapid mobility, continuous data flow across connected nodes, and dynamic network design in a distributed network environment. Distributed Denial of Service (DDOS) is one of the most common and dangerous security attacks on connected vehicle networks. Attackers can remotely control malicious nodes that are programmed to attack other nodes known. The compromised nodes are known as botnets, which will constantly flood the target nodes with User Datagram Protocol (UDP) packets, disrupting the target nodes data flow and operation. Hence, the goal of this research is to create and simulate a vehicular bot-based Distributed Denial of Service (DDoS) assault in connected vehicle networks. A simulation-based methodology is implemented to observe the impact of the number of bots, DDoS rate, and maximum bulk packet size on network performance. Using the NS-3 network simulator, 73 random mobile vehicle nodes with up to 100 vehicle bots were simulated, and the results are discussed. Regardless of the computational constraints, the findings from this study adds to understanding the risks and problems associated with data transmission by analyzing the impact of vehicular bot-based DDoS attacks on connected vehicle performance. Doi: 10.28991/HIJ-2023-04-04-014 Full Text: PDF

BACKGROUND: Spatial disorientation (SD) remains a stubborn and formidable challenge among rotary wing (RW) aircrews, particularly during times of high workload and deceptive visual cues. With tri-Service agreement, British RW Forces employ a layered training approach that now includes simulator-based immersive scenarios.METHODS: Ten bespoke RW SD training scenarios were developed for the AW159 Wildcat helicopter simulator by a multidisciplinary team. Scenarios were embedded within advanced training packages that were not solely focused on SD. A voluntary, anonymous survey instrument was distributed post-SD sortie to assess hazard awareness, training effectiveness, role and mission relevance, and perceived ability to respond to future SD threat. A corresponding assessment from the simulator instructor was used for independent determination if the crew became disoriented during the training.RESULTS: Over a 6-mo training cycle, 69 surveys were completed. Seven-point Likert-scale assessments yielded elevated median scores (6.0, respectively) across all four categories, suggesting favorable aircrew perceptions of training objective success. Elevated scoring of previous SD training received suggests good penetrance among the RW community surveyed. Of all sorties flown, the majority of aircrew (68%) became disoriented at some point during the sortie.DISCUSSION: This report provides limited evidence in support of bespoke SD training scenarios within a synthetic training environment. The merits include flexible ability to address root causes, provision of an interactive and immersive environment, and compatibility with extant tactics and mission configurations. SD simulator-based training can serve as an important component of a layered, multimodal approach.Bushby AJR, Gaydos SJ. Spatial disorientation scenarios for the AW159 helicopter within a synthetic training environment. Aerosp Med Hum Perform. 2023; 94(5):377–383.

In this research we built a SystemC Level-1 data cache system in a distributed shared memory architectural environment, with each processor having its own local cache. Using a set of Fast-Fourier Transform and Random trace files we evaluated the cache performance, based on the number of cache hits/misses, of the caches using snooping and directory-based cache coherence protocols. A series of experiments were carried out, with the results of the experiments showing that the directory-based MOESI cache coherency protocol has a performance edge over the snooping Valid-Invalid cache coherency protocol.

Distributed massive multiple-input multiple-output (D-mMIMO) is one of the key candidate technologies for future wireless networks. A D-mMIMO system has multiple, geographically distributed, access points (APs) jointly serving its users. First of all, this paper reports on where to position these APs to minimize the overall transmit power in actual deployments. As a second contribution, we show that it is essential to take into account both the radiation pattern of the antenna array and the environment information when optimizing AP placement. Neglecting the radiation pattern and environment information, as generally assumed in the literature, can lead to a power penalty in the order of 15 dB and 20 dB, respectively. These results have been obtained by formulating the AP placement optimization problem as a combinatorial optimization problem, which can be solved with different approaches where different channel models are applied. The proposed graph-based channel model drastically lowers the computational time with respect to using an ray-tracing simulator (RTS) for channel evaluation. The performance of the graph-based approach is validated via the RTS, showing that it achieves 5 dB power saving on average compared with a Euclidean distance-based approach, which is the most commonly used approach in the literature.

Abstract In many distributed computing systems, aspects related to security are getting more and more relevant. Security is ubiquitous and could not be treated as a separated problem or a challenge. In our opinion it should be considered in the context of resource management in distributed computing environments like Grids and Clouds, e.g. scheduled computations can be much delayed because of cyber-attacks, inefficient infrastructure or users valuable and sensitive data can be stolen even in the process of correct computation. To prevent such cases there is a need to introduce new evaluation metrics for resource management that will represent the level of security of computing resources and more broadly distributed computing infrastructures. In our approach, we have introduced a new metric called reputation, which simply determines the level of reliability of computing resources from the security perspective and could be taken into account during scheduling procedures. The new reputation metric is based on various relevant parameters regarding cyber-attacks (also energy attacks), administrative activities such as security updates, bug fixes and security patches. Moreover, we have conducted various computational experiments within the Grid Scheduling Simulator environment (GSSIM) inspired by real application scenarios. Finally, our experimental studies of new resource management approaches taking into account critical security aspects are also discussed in this paper.

Distributed renewable energy offers an exciting opportunity for sustainable transition and climate change mitigation. However, it is overlooked in most of the conventional tradable green certificates programs. Blockchain shows an advantage of incorporating a galaxy of distributed prosumers in a transparent and low-cost manner. This paper proposes I-Green, a blockchain-based individual green certificates system for promoting voluntary adoption of distributed renewable energy. Combing the features of blockchain technology and the theories of social norm and peer effects, the novel green ratio incentive scheme and proof of generation consensus protocol are designed for I-Green. A blockchain simulator is constructed to evaluate the effectiveness and efficiency of I-Green system. The simulation results present its potential for facilitating widespread adoption of distributed generation, and confirm the feasibility of blockchain as the information communication technology (ICT).

The spacecraft propulsion system is used for geosynchronous orbit transfer, three-axis stabilization and station-keeping. In order to investigate the system dynamics of spacecraft propulsion system with complex pressurization pipelines and propellant supply pipelines, a modular and extensible simulator UPSSim was developed. The pressurant pipelines were separated into several nodes, each node used lumped parameter model; while the propellant feed pipelines used distributed parameter model. Heat transfer between components and environment was also taken into account. The model accurately predicts the transient behavior of the spacecraft propulsion system during start-up and shutdown process, as well as the effect of pipe initial pressure on the priming waterhammer amplitude. The simulation result demonstrates the adequacy of the modular modeling methodology for spacecraft propulsion system dynamic simulation.

Rain impact energy harvesting has proven to be a feasible and potent source of alternative energy. This paper presents the development of a dynamical model for rain impact energy harvester using a piezoelectric beam in simulated rain environment. Most of the conducted works in literature were based on single droplet impact with fixed height and drop position. The main contribution of this paper is to extend the single droplet impact dynamical model by incorporating random drop sizes and drop positions. In this work, a rain simulator is used to generate artificial rain of different rain rates. Following our previous works, the water accumulation on the piezoelectric beam is modeled using added mass coefficient, and impact coefficient is integrated into the dynamical model to describe the post-impact dynamics of the droplet impact. The stochastic nature of the artificial rain is described using rain rate and drop size distribution. Two random number generators are integrated into the model, which are lognormally and uniformly distributed, to generate random numbers for droplet diameter and drop position respectively. The accuracy of the theoretical model is validated experimentally by considering four different rain rates.

The enhancement in electric power quality using a single-stage solar PV integrated Unified Power Quality Conditioner (UPQC) has been discussed in this paper. The UPQC is the combination of Distributed static compensator (DSTATCOM) and Dynamic Voltage Restorer (DVR) having the common DC voltage supply link. The DSTATCOM compensates for the load current associated problems like load power factor improvement, even and odd current harmonics elimination etc. Also, it performs the additional work of transferring power from the solar PV system to the load of the distribution system. The DVR compensates the voltage-associated power quality problems like source voltage sag, source voltage swell, and voltage distortion. Discussed UPQC with distributed generation system works on modified synchronously rotating reference frame theory. With the help of the discussed system, the two outcomes are achieved such as clean and renewable energy generation and power quality enhancement. The system is designed in MATLAB Simulink environment and then system performance is verified on Real-Time Digital Simulator (OPAL-RT OP4510) in Software in Loop Simulation (SIL) and Hardware in Loop Simulation (HIL) platforms.

Abstract. Hydrological modeling is a crucial component in hydrology research, particularly for projecting future scenarios. However, achieving reproducibility and automation in distributed hydrological modeling research for modeling, simulation, and analysis is challenging. This paper introduces rSHUD v2.0, an innovative, open-source toolkit developed in the R environment to enhance the deployment and analysis of the Simulator for Hydrologic Unstructured Domains (SHUD). The SHUD is an integrated surface–subsurface hydrological model that employs a finite-volume method to simulate hydrological processes at various scales. The rSHUD toolkit includes pre- and post-processing tools, facilitating reproducibility and automation in hydrological modeling. The utility of rSHUD is demonstrated through case studies of the Shale Hills Critical Zone Observatory in the USA and the Waerma watershed in China. The rSHUD toolkit's ability to quickly and automatically deploy models while ensuring reproducibility has facilitated the implementation of the Global Hydrological Data Cloud (https://ghdc.ac.cn, last access: 1 September 2023), a platform for automatic data processing and model deployment. This work represents a significant advancement in hydrological modeling, with implications for future scenario projections and spatial analysis.

With an electrical grid shifting toward Distributed Generation (DG), the emerging use of renewable energy resources is continuously creating challenges to maintain an acceptable electrical power quality thought-out the grid; Therefore, in an energy market where loads are becoming more and more sensitive in a distributed generation filled with polluting nonlinear loads, power quality improvement devices such Active Power Filters (APFs) have to evolve to meet the new standards, since theirs conventional control strategies can't properly operate when multiple power quality problems happens at once, even the one using AI based control as it will be proven in this paper. In this paper a neural network based Active Power Filter will be tested in a DG environment where both current and voltage harmonics, along with fast frequency variation occurs, we will see how the PLL can downgrade its performances enormously under such hostile conditions, We propose to solve this problem by replacing the conventional PLL with a nonlinear least square (NLS) frequency estimator, this novel NLS-ADALINE SAPF is immune in high DG penetration environment, as it will be tested and validated experimentally on an Opal-RT OP5600 FPGA based real-time simulator.