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This study addresses three primary objectives related to lumbar intervertebral disc (IVD) biomechanics under ramping quasi-static loading conditions. First, we explore the conditions justifying the simplification of axisymmetric elastic fiber families into single fiber bundles through discretized strain energy functions. Simulations reveal that a concentration factor exceeding 10 allows for a consistent deviation below 10% between simplified and non-simplified responses. Second, we investigate the impact of elastic fibers on the physiological stiffness in IVDs, revealing minimal influence on biological motions but significant effects on degeneration. Lastly, we examine the initiation and progression of annulus fibrosus (AF) damage. Our findings confirm the validity of simplifying elastic fiber families and underscore the necessity of considering elastic fiber damage in biomechanical studies of AF tissues. Elastic fibers contribute to increased biaxial stretch stiffness, and their damage significantly affects the loading capacity of the inner AF. Additionally, degeneration significantly alters the susceptibility to damage in the AF, with specific regions exhibiting higher vulnerability. Damage tends to extend circumferentially and radially, emphasizing the regional variations in collagen and elastic fiber properties. This study offers useful insights for refining biomechanical models, paving the way for a more comprehensive understanding of IVD responses and potential clinical implications. [Display omitted] • Validated conditions for simplifying elastic fiber families for efficient modeling. • Revealed elastic fibers' significant role in enhancing biaxial stretch stiffness. • Unveiled both initiation and progression modes of AF damage under typical motions. • Disc degeneration greatly affects motions and initiates distinct damage patterns. • The posterior outer AF is more susceptible to damage than the anterior inner area. [ABSTRACT FROM AUTHOR]

In the context of digitization and industry 4.0, the production-related disciplines developed powerful simulation models with different scopes and varying levels of detail. As these simulation systems are usually not built in a compatible way, the models cannot be combined easily. Co-simulation techniques provide a promising basis for combining these models into one superordinate model and utilizing it for planning new factories, adapting existing ones or for production planning. However, today's co-simulation systems do not benefit from the inherent flexibility of the represented production systems. Simulation-based optimization is carried out inside each discipline's simulation system, which means that interdisciplinary, global optima are often impossible to reach. Additionally, the aspect of human interaction with such complex co-simulation systems is often disregarded. Addressing these two issues, this paper presents a concept for combining different simulation models to interdisciplinary multi-level simulations of production systems. In this concept, the inherent flexibilities are capitalized to enhance the flexibility and performance of production systems. The concept includes three hierarchical levels of production systems and allows human interaction with the simulation system. These three levels are the Process Simulation level, the Factory Simulation level, and the Human Interaction level, but the concept is easily extendable to support additional levels. Within the multi-level structure, each simulation system carries out a multi-objective optimization. Pareto-optimal solutions are forwarded to simulations on higher hierarchical levels in order to combine them and meet flexibly adaptable objectives of the entire production system. The concept is tested by means of a simplified production system, to optimize it in terms of throughput time and electric energy consumption. Results show that the presented interdisciplinary combination of heterogeneous simulation models in multi-level simulations has the potential to optimize the productivity and efficiency of production systems. [ABSTRACT FROM AUTHOR]

In this paper, a methodology is presented and employed for simulating the Internet of Things (IoT). The requirement for scalability, due to the possibly huge amount of involved sensors and devices, and the heterogeneous scenarios that might occur, impose resorting to sophisticated modeling and simulation techniques. In particular, multi-level simulation is regarded as a main framework that allows simulating large-scale IoT environments while keeping high levels of detail, when it is needed. We consider a use case based on the deployment of smart services in decentralized territories. A two level simulator is employed, which is based on a coarse agent-based, adaptive parallel and distributed simulation approach to model the general life of simulated entities. However, when needed a finer grained simulator (based on OMNeT++) is triggered on a restricted portion of the simulated area, which allows considering all issues concerned with wireless communications. Based on this use case, it is confirmed that the ad-hoc wireless networking technologies do represent a principle tool to deploy smart services over decentralized countrysides. Moreover, the performance evaluation confirms the viability of utilizing multi-level simulation for simulating large scale IoT environments. [ABSTRACT FROM AUTHOR]

Hybrid lightweight parts aim at improving the economical and ecological performance of automobiles by reducing weight and, consequently, CO 2 emissions. The environmental advantageousness requires careful attention during the car's design phase to prevent problem shifting from use phase into production. Due to the degree of novelty of hybrid components, reliable data about energy and resource demands in production is not yet available. This work presents a multi-level simulation framework for coupling models from different disciplines in order to derive LCA-relevant data. Exemplarily, a discrete-event process chain simulation is connected with a physical process model for a forming process. [ABSTRACT FROM AUTHOR]

Abstract: For the simulation of structural collapse using controlled explosives, the quantification of structural parameters has to be accomplished on the basis of only few data, which may additionally be characterized by vagueness, e.g. due to uncertain measurements or changing reproduction conditions. To ensure a reliable prediction of a structural collapse, next to a close to reality simulation of the complex dynamic process, this uncertainty has to be taken into account. With regard to very high computation associated with the simulation of collapses of real world structures based on conventional finite element models, this paper addresses an efficient approach for the simulation of structural collapse based on multibody models, that simultaneously allow for the investigation of uncertainty. [Copyright &y& Elsevier]

In this paper, a formal engineering design synthesis methodology based on evolutionary computation is presented, with special emphasis on the design and optimization of distributed independent systems. A case study concerned with design of a sensory system for traffic monitoring purposes is presented, along with simulations of traffic scenarios at several levels of abstraction. It is shown how the methodology introduced is able to deal with the engineering design challenges present in the case study, and effectively synthesize novel design solutions of good quality. Moreover, when the fitness function is formulated as an aggregation of design preferences with different weights and trade-off strategies, the complete Pareto optimal frontier can be determined by the evolutionary synthesis methodology. The results of this study suggest that the approach can be useful for designers to solve challenging engineering design synthesis problems. [ABSTRACT FROM AUTHOR]

Typically differential equations are employed to simulate cellular dynamics. To develop a valid continuous model based on differential equations requires accurate parameter estimations; an accuracy which is often difficult to achieve, due to the lack of data. In addition, processes in metabolic pathways, e.g. metabolite channeling, seem to be of a rather qualitative and discrete nature. With respect to the available data and to the perception of the underlying system, a discrete rather than a continuous approach to modeling and simulation seems more adequate. A discrete approach does not necessarily imply a more abstract view on the system. If we move from macro to micro and multi-level modeling, aspects of subsystems and their interactions, which have been only implicitly represented, become an explicit part of the model. To start exploring discrete event phenomena within metabolite channeling we choose the tryptophan synthase. Based on a continuous macro model, a discrete event, multi-level model is developed which allows us to analyze the interrelation between structural and functional characteristics of the enzymes. [Copyright &y& Elsevier]

This paper presents the issue of dynamic multi-level simulation of hardware designs that addresses the problem of inefficiency associated with the conventional static multi-level simulation ap proaches as in ADLIB-SABLE (Hill 1980), DIANA (Demou and Arnout 1979), and SPLICE (Newton 1978). In this approach, digital sim ulation or verification (McWilliams 1980) of hardware designs is initiated at a high level of abstraction. When detailed results are required for one or more high-level components or for tracing the source of an error to any of the lower-level devices, the appropriate components are expanded into their lower-level implementations. Then simulation or verification initiates at that level. Following completion of execution at the lower level, con trol returns to the higher level. Consequently, only those sub parts of a digital design are selected for expansion and detailed simulation that are dynamically warranted by the higher-level simulation results. Unnecessary simulation effort may be elimi nated. Dynamic multi-level simulation or zooming is a generaliza tion of the swapping technique (Szygenda 1973) to functional and fault simulation and timing verification and to the differ ent abstraction levels in the hierarchy between the gate- and behavior-levels. This paper also addresses the implementation of zooming in the rule-based design verifier, RDV (Ghosh 1984), at Stanford University. That RDV uses Ada (U.S. Dept. of Defense 1983) as a hardware description language and simulation envi ronment (Ghosh 1985). [ABSTRACT FROM PUBLISHER]