Modeling and Simulation Method of Component Based Petri Net

We argue here that, in recent years, the world's financial markets have become a globally interconnected complex adaptive ultra-large-scale socio-technical system-of-systems, and that this has important consequences for how the financial markets should be engineered and managed in future. Major failures in the financial markets can now occur at super-human speeds, as was witnessed in the of May 6th 2010. Events such as the Flash Crash may become more commonplace in future, unless lessons are learned from other fields where complex adaptive socio-technical systems-of-systems have to be engineered for high-integrity, safety-critical applications. In this document we review the literature on failures in risky technology and high-integrity approaches to safety-critical SoS engineering. We conclude with an argument that, in the specific case of the global financial markets, there is an urgent need to develop major national strategic modeling and predictive simulation capabilities, comparable to national-scale meteorological monitoring and modeling capabilities. The intent here is not to predict the price-movements of particular financial instruments or asset classes, but rather to provide test-rigs for principled evaluation of systemic risk, estimating probability density functions over spaces of possible outcomes, and thereby identifying potentially high-consequence failure modes in the simulations, before they occur in real life, by which time it is typically too late.

This paper provides an overview of the tools used to conduct independent modeling and simulation of Artemis 1 separation events and highlights challenges and lessons learned across a decade of analysis. An overview of each of the tools along with the process flow and key components of maintaining independence from the Program’s baseline tool set will be provided. In addition, each of the separation analyses conducted will be discussed, making note of key models incorporated for each event and unique challenges that were addressed. The technical work described in this paper is part of an on-going technical assessment conducted by the NASA Engineering and Safety Center to develop and maintain an independent modeling and simulation capability in support of Space Launch System (SLS) and Multi-Purpose Crew Vehicle (MPCV) throughout design, verification, and flight readiness cycles. For Artemis 1, an end-to-end analysis approach was taken with events simulated from launch to re-entry. This paper will focus on the separation events, including liftoff clearance analysis, solid rocket booster (SRB) separation from Core Stage (CS), Service Module (SM) panel jettison, ICPS / Core Stage Separation, and MPCV/ ICPS separation. To assess separation clearances, the NESC has developed a high fidelity, independent 6-degree of freedom (DOF) simulation of the separation events. The simulation was developed using the Program to Optimize Simulated Trajectories II (POST2). POST2 is an industry standard flight trajectory optimization and simulation tool that is Class D compliant and follows NASA NPR 7150.2, which includes regression testing, unit testing, and configuration control of the simulation. The primary objective of the SLS separation and clearance analyses was to estimate the clearances between different vehicle components and/or ground support equipment (GSE) during separation events. The clearance is defined as the minimum distance from any point on one 3D geometry model associated with one vehicle component (or GSE) to any point on another 3D geometry model associated with a vehicle component separating from the main body. The vehicle geometry models used by the NESC to compute the separation clearances were derived from CAD models. POST2 simulation results were post processed in the Exploration Visualization Environment (EVE) tool to compute clearances, and detect recontact occurrences, if any, between the separating stages. EVE is a simulation, visualization, and analysis system designed to integrate time-based dynamics data with detailed graphical models in a full-scale virtual environment. EVE was used to simultaneously calculate more than 30 different separation clearances by “driving” detailed vehicle geometry models with position and attitude time history data obtained from the POST2 simulation. EVE displays each clearance distance visually, at any given instant of time, with a straight line connecting the two closest points on each object and records the time history of the clearance distance in a file. If the clearance reduces to zero, then EVE reports it as a recontact. To perform separation analyses, POST2 Monte Carlo analyses were performed by running 2000 dispersed cases that included over hundreds of uncertainties and dispersions for a range of simulation models including aerodynamics, propulsion, navigation sensors, control actuators, slosh and flexible body dynamics, and winds and atmosphere. Clearances were computed for each of the dispersed Monte Carlo trajectories and overall separation performance was statistically assessed. Over the past decade the POST2 simulation and EVE visualization tools have been used to perform detailed assessments of the separation events that occur during the Artemis 1 ascent. To support these assessments, numerous unique simulation models were developed and integrated into the standard suite of POST2 simulation models to address and resolve key concerns specific to each of the Artemis 1 separation events. In addition to presenting an overview of the multi-body 6-DOF simulation and separation analysis capability, the paper will discuss the integration of key simulation models such as flexible body dynamics, slosh dynamics, separation mechanisms, multi-body aerodynamics, and environmental models. Additional details are provided about other challenges that were addressed, including the use of a convex hull to reduce computational time for clearance calculations, the modeling of incidental recontact during separation events, and the capability to simulate failure scenarios.

Modeling and simulation challenges pursued by the Consortium for Advanced Simulation of Light Water Reactors (CASL)

Microreactors are small mobile transportable nuclear reactors with thermal power less than 20 MWt that are designed to meet the needs of remote areas, military installations, emergency operations, and disaster relief zones. These reactor are concepts that are intended to be factory-manufacturable, easily transportable, and will allow for semi- or full-autonomous operation. To assist with development of microreactors, modeling and experimentation need to be performed with verification and validation to gain confidence in the models and tools. The objective of this study is apply advanced modeling and simulation capabilities being developed by the DOE Office of Nuclear Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to perform integrated modeling and simulation capability for multiphysics simulation of the microreactor concepts. This activity will provide an opportunity to exercise the codes to provide both gain experience and to provide feedback to the developers.

Simulation of the interaction between an urban drainage system (UDS) and surface flow is a challenging issue. Conventional rainfall–runoff models are only able to simulate the flow in UDSs without considering the interaction between surface runoff and UDS. In this study, SWMM (storm water management model), as a well‐known urban drainage simulation model, and a two‐dimensional overland flow model developed based on the cellular automata approach, have been coupled for UDS simulation. In the proposed model, sewer flows are one‐dimensionally simulated using the SWMM model and at the flooded manholes, the surcharge hydrographs are determined. Then the two‐dimensional overland flow model is used for routing the surcharged flows. The coupled model could consider the complex interaction between the drainage system and the overland flow. The proposed model has been used in a study area located in Tehran, capital of Iran. The results show that almost 40% of surcharged flow returns back to the UDS, which caused 1.5% increase in the UDS's outflow volume. This can greatly affect the UDS performance downstream of the study area. The implementation results show the model's capability in simulation of flood behaviour as well as the urban inundated area with acceptable accuracy and much less computational effort. Copyright © 2017 John Wiley & Sons, Ltd.

A domain structure and its dynamic transformation in a rotating magnetic field are experimentally studied over a wide induction range (up to 1.7 T) on a single-crystal plate whose surface deviates through angle β from a (110) crystallographic plane. The induction ranges of different dynamic behavior of the domain structure are determined. At an induction below 0.5 T, the magnetization reversal of the plate occurs via a change in the main domain structure. At inductions up to 1.4 T, the main structure undergoes strong dynamic fragmentation. At a higher induction, the magnetization reversal of the sample proceeds via the growth of the closure structure localized at the periphery of the sample in the absence of a magnetic field. The dependences obtained support the early considerations regarding the behavior of magnetic losses.

Topicality. Military threats determined the significant pace of changes in the risks of mixed cargoes transportation and proved the need for new methods of ensuring the reliability of transportation. First of all, there was the problem of assessing the levels of transportation reliability along individual routes and modeling a possible change of routes with the choice of safer options and ways of transportation. A particularly important function of such a model, due to the rapid pace of changes in risks, is the possibility of its practical application in real-time conditions.Aim and tasks. The purpose of the work is to develop a mathematical model of mixed cargo transportation in the conditions of dynamic changes in risks to increase the reliability of the transportation process, analyze alternative options for transportation, and identify opportunities for changing the route even in the process of cargo transportation. Achieving the goal of the study made it necessary to set and solve the following tasks: to implement the possibility of analyzing alternative transportation options and proposing route changes in real time; prove the capabilities of the developed model on the example of specific enterprises; to ensure reliability forecasting of the next cargo transportation stages; implement the possibility of optimizing multi-purpose tasks to ensure reliability, minimize the cost and time of transportation; to stratify the reliability of cargo transportation according to the level of threats probability. Materials and methods. Various general and special methods of knowledge were used in the work: the method of quantitative and qualitative comparison for the stratification of the cargo transportation reliability depending on the risks at individual stages; methods of vector analysis to take into account the probability of the cargo transportation risk at each stage of mixed transportation; the method of induction and deduction made it possible to consider the reliability of the transportation as the reciprocal of the transportation risk probability; the task fragmentation method allows to include probable stages of transportation in different transport routes; a method of mathematical formalization of the problem for the formation of a model of mixed cargo transportation using water transport in conditions of dynamic changes in risks. Research results. A mathematical model of mixed cargo transportation in conditions of dynamic changes in risks was developed to increase the reliability of transportation, analyze alternative transportation options, and identify opportunities for changing the route during cargo transportation. To solve this, the following tasks were developed: a mathematical model capable of analyzing alternative transportation options and proposing route changes in real life was developed; proven possibilities of the model on the example of specific enterprises; forecasting of the reliability the next cargo transportation stages is ensured; the possibility of optimizing multi-purpose tasks to ensure reliability, minimizing the cost and time of transportation has been implemented; stratification of the reliability cargo transportation by the level of probability threats was carried out. Conclusion. Using the model, the activities of enterprises that transported their products through the ports of the Sea of Azov were analyzed. Due to the decrease in the reliability of cargo transportation through the Kerch Strait, alternative routes for the transportation of mixed cargo are proposed, for the use of "river-sea" vessels at certain stages. Approbation of the model for increasing the efficiency of the transport and logistics process of enterprises proved its effectiveness. The use of the developed mathematical model for the analysis of enterprise activity indicated an implicit advantage of increasing the level of transportation reliability, in particular, in relation to identifying the possibility of reducing warehouse stocks with a significant saving of working capital at the same time. The presented results of the research make it possible to ensure the proper reliability of transportation of mixed cargoes, even in conditions of significant dynamic changes in the level of threats on transportation routes.

Since inception of the DOE-NE Integrated Energy Systems (IES) program, several program and modeling visions and roadmaps have been published. In 2020, a last comprehensive roadmap for the DOE-NE Integrated Energy Systems program was published. In 2017, a separate modeling and simulation capability development plan was published that was extensively updated in 2022. The current report incrementally updates the 2022 modeling and simulation capability roadmap. This is not a new report, but individual sections have been updated to reflect recent accomplishments and new directions of the program. The role of modeling and simulation within IES is to support the demonstration of new coupled integrated technologies along every step of the technology maturation from the strategic analysis of preferred system architecture to preliminary design, to laboratory testing, up to full commercial testing and integration. To achieve this role, modeling and simulation must be able to assess the technical performance and the economic viability of potential IES. Also, modeling and simulation must provide support for experimental evaluations (i.e., support component design and real-time operations of experimental demonstration systems). Finally, modeling and simulation can help scale-up experimental systems to the final commercial systems. This report details the current state of the modeling and simulation efforts within IES for the above-mentioned areas, provides a gap analysis, and proposes next steps for a time horizon over the next years.

This project addresses three important gaps in existing evaluated nuclear data libraries that represent a significant hindrance against highly advanced modeling and simulation capabilities for the Advanced Fuel Cycle Initiative (AFCI). This project will: Develop advanced theoretical tools to compute prompt fission neutrons and gamma-ray characteristics well beyond average spectra and multiplicity, and produce new evaluated files of U and Pu isotopes, along with some minor actinides; Perform state-of-the-art fission cross-section modeling and calculations using global and microscopic model input parameters, leading to truly predictive fission cross-sections capabilities. Consistent calculations for a suite of Pu isotopes will be performed; Implement innovative data assimilation tools, which will reflect the nuclear data evaluation process much more accurately, and lead to a new generation of uncertainty quantification files. New covariance matrices will be obtained for Pu isotopes and compared to existing ones. The deployment of a fleet of safe and efficient advanced reactors that minimize radiotoxic waste and are proliferation-resistant is a clear and ambitious goal of AFCI. While in the past the design, construction and operation of a reactor were supported through empirical trials, this new phase in nuclear energy production is expected to rely heavily on advanced modeling and simulation capabilities. To be truly successful, a program for advanced simulations of innovative reactors will have to develop advanced multi-physics capabilities, to be run on massively parallel super- computers, and to incorporate adequate and precise underlying physics. And all these areas have to be developed simultaneously to achieve those ambitious goals. Of particular interest are reliable fission cross-section uncertainty estimates (including important correlations) and evaluations of prompt fission neutrons and gamma-ray spectra and uncertainties.

Accelerator facility upgrades, new accelerator applications, and future design efforts are leading to novel klystron and IOT device concepts, including multiple beam, high-order mode operation, and new geometry configurations of old concepts. At the same time, a new simulation capability, based upon finite-difference “cut-cell” boundaries, has emerged and is transforming the existing modeling and design capability with unparalleled realism, greater flexibility, and improved accuracy. This same new technology can also be brought to bear on a difficult-to-study aspect of the energy recovery linac (ERL), namely the accurate modeling of the exit beam, and design of the beam dump for optimum energy efficiency. We have developed new capability for design calculations and modeling of a broad class of devices which convert bunched beam kinetic energy to RF energy, including RF sources, as for example, klystrons, gyro-klystrons, IOT's, TWT’s, and other devices in which space-charge effects are important. Recent advances in geometry representation now permits very accurate representation of the curved metallic surfaces common to RF sources, resulting in unprecedented simulation accuracy. In the Phase I work, we evaluated and demonstrated the capabilities of the new geometry representation technology as applied to modeling and design of output cavity components of klystron, IOT's, and energy recovery srf cavities. We identified and prioritized which aspects of the design study process to pursue and improve in Phase II. The development and use of the new accurate geometry modeling technology on RF sources for DOE accelerators will help spark a new generational modeling and design capability, free from many of the constraints and inaccuracy associated with the previous generation of “stair-step” geometry modeling tools. This new capability is ultimately expected to impact all fields with high power RF sources, including DOE fusion research, communications, radar and other defense applications.

Dynamic secondary structural changes in Ca2+-saturated calmodulin upon interaction with the antagonist, W-7

Vertical-axis wind turbines (VAWTs) have a long history, with a wide variety of turbine archetypes that have been designed and tested since the 1970s. While few utility-scale VAWTs currently exist, the placement of the generator near the turbine base could make VAWTs advantageous over tradition horizontal-axis wind turbines for floating offshore wind applications via reduced platform costs and improved scaling potential. However, there are currently few numerical design and analysis tools available for VAWTs. One existing engineering toolset for aero-hydro-servo-elastic simulation of VAWTs is the Offshore Wind ENergy Simulator (OWENS), but its current modeling capability for floating systems is non-standard and not ideal. This article describes how OWENS has been coupled to several OpenFAST modules to update and improve modeling of floating offshore VAWTs and discusses the verification of these new capabilities and features. The results of the coupled OWENS verification test agree well with a parallel OpenFAST simulation, validating the new modeling and simulation capabilities in OWENS for floating VAWT applications. These developments will enable the design and optimization of floating offshore VAWTs in the future.

A vital part of the licensing process for advanced (non-LWR) nuclear reactor developers in the United States is the assessment of the reactor’s source term, i.e., the potential release of radionuclides from the reactor system to the environment during normal operations and accident sequences. In comparison to source term assessments which follow a bounding approach with conservative assumptions, a mechanistic approach to modeling radionuclide transport, which realistically accounts for transport and retention phenomena, is expected to be used for advanced reactor systems. As the designs of advanced reactors increase in maturity and progress towards licensing, there is a need to advance modeling and simulation capabilities in analyzing the mechanistic source term (MST) of a prospective reactor concept. In the present work, a survey is provided of existing computational capabilities for the modeling of advanced reactors MSTs. The following reactors are considered: high temperature gas reactors (HTGR); molten salt reactors (MSR) which include salt-fueled reactors and fluoride salt-cooled high temperature reactors (FHR); and sodium- and lead-cooled fast reactors (SFR, LFR). A review of relevant codes which may be useful in providing information to MST analyses is also completed, including codes that have been used for source term analyses of LWRs, as well as those being developed for other aspects of advanced reactor system modeling such as reactor physics, thermal hydraulics, and chemistry. A discussion of MST modeling capabilities for each reactor type is provided with additional focus on important phenomena and functional requirements. Additionally, a comprehensive survey is provided of tools for consequence modeling such as atmospheric transport and dispersion (ATD).

The pebble bed reactor is a unique reactor design due to its capacity for continuous multipass circulation of the fuel elements, without causing interruption to reactor operation, with the assistance of the burnup measurement system. Such a system necessarily requires an accurate knowledge of the burnup of each fuel pebble upon ejection from the core so as to inform the reloading decision and to ensure that no pebble exceeds the regulated discharge burnup limit at any point following reinsertion into the reactor core. In this work, we conceptualize, develop, and demonstrate a machine learning–based fuel burnup prediction framework leveraging advanced modeling and simulation capabilities. At its core, machine learning regression models are learned from simulated data to establish the correlation among the irradiated fuel composition (hence burnup), the gamma leakage spectrum, and the gamma spectroscopy results. Sensitivity analysis is conducted to quantify the impact of unknown design parameters, such as fuel enrichment, and irradiation environment, including power density, temperature, and neighboring materials, on the prediction accuracy of various supervised regression algorithms. The effects of a short cooldown period on machine learning prediction accuracy are also investigated. A test data set is used to validate that the data generation methodology proposed in this work successfully results in a machine learning model capable of interpolating its prediction of burnup onto a much wider range of irradiation conditions than were explicitly represented in the training database. The inclusion of a cooldown period of just 2 h leads to a prediction root-mean-square error of <5 MWd/kgU when the fuel enrichment is known and <9 MWd/kgU otherwise.

The successful development of various electro-optical systems is highly dependent on precise electronic circuit design which must account for possible parameter drift in the various piece parts. The utilization of a comprehensive computer analysis program (SYSCAP) provides the electro-optical system designer and electro-optical management organization with a well-structured tool for a comprehensive system analysis'. As a result, the techniques described in this paper can be readily used by the electro-optical design community. An improved version of the SYSCAP computer program (version 2.5) is presented which inncludes the following new advances: (1) the introduction of a standard macro library that permits call-up of proven mathematical models for system modeling and simulation, (2) the introduction of improved semiconductor models for bipolar junction transistors and p-n junctions, (3) multifunction modeling capability to link signals with very high speed electronic circuit models, (4) high resolution computer graphics (both interactive and batch process) for display and permanent records, and (5) compatibility and interface with ad-vanced engineering work stations. This 2.5* version of the present SYSCAP 2 computer analysis program will be available for use through the Control Data Corporation world-wide Cybernet system in 1983*. This paper provides an overview of SYSCAP modeling and simulation capabilities.