History of Simulation

Zeigler, Bernard P.; França, Breno Bernard Nicolau de; Neto, Valdemar Vicente Graciano; Hill, Raymond R.; Champagne, Lance; Ören, Tuncer I.

doi:10.1007/978-3-031-11085-6_17

Cited by 4 publications

(4 citation statements)

References 59 publications

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“…In general, due to the dynamic nature of DTs, V&V should be a continuous process (either online or offline) that needs to be performed periodically (or on-demand). 38 Sargent stated that V&V of a basic simulation model comprises four pillars: (1) Conceptual Model Verification, (2) Computerized Model Validation, (3) Operational Validation, and (4) Data Validation. 75 Lugaresi et al 38 presented the DT V&V approach based on the following four levels: (1) Logic-level Validation (Digital Model), (2) Input-level Validation (Input Data), (3) Event-level validation (System Events), and (4) Performance-level Validation (KPIs).…”

Section: Ref System Interoperabilitymentioning

confidence: 99%

“…Computer simulation has its roots in the computational experiments of neutron scattering developed by Ulam and Von Neumann, who developed the Monte Carlo method. 1,2 Since then, researchers have made many foundational contributions to M&S. The number of applications of simulations to solve real-world problems is even many times more. Computational science has even been called the third pillar of science for that reason.…”

Section: Introductionmentioning

confidence: 99%

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From modeling and simulation to Digital Twin: evolution or revolution?

Ali,

Biglari,

Denil

et al. 2024

SIMULATION

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As digitalization is permeating all sectors of society toward the concept of “smart everything,” and virtual technologies and data are gaining a dominant place in the engineering and control of intelligent systems, the Digital Twin (DT) concept has surfaced as one of the top technologies to adopt. This paper discusses the DT concept from the viewpoint of Modeling and Simulation (M&S) experts. It both provides literature review elements and adopts a commentary-driven approach. We first examine the DT from a historical perspective, tracing the historical development of M&S from its roots in computational experiments to its applications in various fields and the birth of DT-related and allied concepts. We then approach DTs as an evolution of M&S, acknowledging the overlap in these different concepts. We also look at the M&S workflow and its evolution toward a DT workflow from a software engineering perspective, highlighting significant changes. Finally, we look at new challenges and requirements DTs entail, potentially leading to a revolutionary shift in M&S practices. In this way, we hope to foster the discussion on DTs and provide the M&S expert with innovative perspectives.

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Section: Ref System Interoperabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

From modeling and simulation to Digital Twin: evolution or revolution?

Ali,

Biglari,

Denil

et al. 2024

SIMULATION

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“…SOM models are typically based on empirical or mechanistic approaches that help in predicting the future SOM trends [30,105,106]. The development and advancement in soil organic matter modeling from simple exponential decay functions, more complex functions with substrate concentration and time-dependent relative decomposition rate, and simple regression equations to more complex processes-based models have been a success in understanding and designing sustainable soils, SOM, crops, and climate management practices [23,47,75,104,107]. The progress in mathematical, computer, and simulation skills has allowed the development of different SOM analytical and simulation models and, as the measurement of the impact of a given management practice to SOM changes requires long-term or extensive short-term data, it is the same for modeling data for reliable re-sults [41][42][43]50].…”

Section: Modeling As a Tool For Sustainable Soil Organic Matter Asses...mentioning

confidence: 99%

“…Most analytical models have historically considered soil organic matter as a single homogeneous pool that decomposes with varying relative rates of decomposition over time. However, advancements in knowledge about computers, modeling, and simulations [46,47] have led to the development of different simulation models. It was not until the 1970s that Hanna Parnas first used a simulation model to describe SOM decomposition, which considered SOM as a heterogeneous mixture of different pools that decompose at varying relative rates over time [42].…”

Section: Introduction Importance and Overview Of The Advances In Eval...mentioning

confidence: 99%

Quantitative Approaches in Assessing Soil Organic Matter Dynamics for Sustainable Management

et al. 2023

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The aim of this study was to provide an overview of the approaches and methods used to assess the dynamics of soil organic matter (SOM). This included identifying relevant processes that describe and estimate SOM decomposition, lability, and humification for the purpose of sustainable management. Various existing techniques and models for the qualitative and quantitative assessment of SOM were evaluated to gain a better understanding of advances in organic matter transformation. This evaluation aimed to identify the strengths, limitations, and applications of these techniques and models, and to highlight new research directions in the field. Quantitative analysis of SOM can be performed using various parameters, including oxidation kinetics, lability, carbon management index, humification degree, humification index, and humification ratio. On the other hand, qualitative evaluation of SOM can involve techniques such as oxidizability, high-performance size-exclusion chromatography, electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry, visual examination, smell, assessment of microorganism content, plant growth, cation exchange capacity, type of organic material, and decomposition. These techniques and parameters provide valuable insights into the characteristics and transformation of SOM, enabling a comprehensive understanding of its dynamics. Evaluating SOM dynamics is of utmost importance as it is a determining factor for soil health, fertility, organic matter stability, and sustainability. Therefore, developing SOM models and other assessment techniques based on soil properties, environmental factors, and management practices can serve as a tool for sustainable management. Long-term or extensive short-term experimental data should be used for modeling to obtain reliable results, especially for quantitative SOM transformation analysis, and changes in the quality and quantity of SOM should be considered when developing sustainable soil management strategies.

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Agent-Based Technologies for Research and Practical Use in Management

Leitner,

Wall

2024

The Oxford Handbook of Agent-Based Computational Management Science

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This chapter examines the role of agent-based modelling and simulation in advancing theories and addressing operational and design issues within the realm of management science. We specifically explore the potential contributions of agent-based modelling and simulation to abductive and deductive reasoning. Through a theoretical lens, we argue that agent-based modelling and simulation is useful in exploring complex dynamics, and it thereby emerges as a potent tool for generating, refining, and selecting hypotheses. It facilitates a deeper understanding of the behaviours within complex adaptive systems—ranging from organizations to networks—thereby enabling the formulation of causally plausible explanations for observed phenomena. This capability is particularly crucial in environments where traditional analytical methods fall short due to inherent complexities. Furthermore, we discuss the role of agent-based modelling and simulation in operationalizing hypotheses for empirical testing, emphasizing its utility in translating theoretical concepts into testable models and identifying the boundary conditions under which these models hold true. In the context of operational and design issues, we argue that agent-based modelling and simulation supports the exploration of means–ends relations and the operationalization of design choices, thereby contributing to the development of innovative solutions and potentially better decision-making within organizations. Thereby, the method substantially contributes to bridging the gap between theory and practice within the field of management science, presenting it as an essential approach for navigating the complexities of contemporary management challenges.

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History of Simulation

Cited by 4 publications

References 59 publications

From modeling and simulation to Digital Twin: evolution or revolution?

From modeling and simulation to Digital Twin: evolution or revolution?

Quantitative Approaches in Assessing Soil Organic Matter Dynamics for Sustainable Management

Agent-Based Technologies for Research and Practical Use in Management

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