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Reduced order modeling of spray drying 喷雾干燥的降阶建模
Q3 Engineering Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.026
A. Lepsien , A. Schaum
Spray drying is a common a technique in process engineering, involving analysis tasks for large-scale multiphysics mechanisms, typically addressed using Computational Fluid Dynamics (CFD) software based on Finite Element Method (FEM) simulation. To enable e.g. real-time control schemes to take into account spatio-temporal behavior, efficient Reduced Order Models (ROMs) need to be identified, which in the best case retain physical information and interpretability as much as possible. In this paper, this problem is approached for a simplified two-dimensional spray dryer CFD model. Two different versions of Dynamic Mode Decomposition with control (DMDc) are compared, namely (i) a direct application of DMDc to snapshot data for temperature and humidity profiles, including droplet populations as moving and distributed inputs, and (ii) an adaptation exploring structure preservation based on the physical insight to the underlying mechanisms. It turns out that for the presented case study the structure preserving DMDc yields improved results.
喷雾干燥是过程工程中常见的一种技术,涉及大规模多物理场机制的分析任务,通常使用基于有限元法(FEM)模拟的计算流体动力学(CFD)软件来解决。为了使实时控制方案能够考虑到时空行为,需要确定有效的降阶模型(ROMs),在最好的情况下,它尽可能保留物理信息和可解释性。本文针对一个简化的二维喷雾干燥机CFD模型,探讨了这一问题。本文比较了两种不同版本的动态模态分解与控制(DMDc),即(i) DMDc直接应用于温度和湿度剖面的快照数据,包括液滴种群作为移动和分布的输入,以及(ii)基于对潜在机制的物理洞察探索结构保存的自适应。结果表明,对于所提出的案例研究,保留DMDc的结构产生了改进的结果。
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引用次数: 0
Limit Cycle Analysis of Guideline-based treated Graves’ Disease Patients 基于指南治疗的Graves病患者的极限环分析
Q3 Engineering Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.043
Thomas Benninger , Martin Horn , Markus Reichhartinger
A brief review of existing medical dosage guidelines for Graves’ disease is conducted. This motivates to derive a recommendation strategy and a performance assessment via limit cycle stability analysis. For this purpose, an existing mathematical treatment model is simplified by incorporating medical aspects. From an application point of view, this is related to suboptimal treatments which can be approximated by a proportional controller in combination with a time-discretization of the closed-loop model for incorporating the effect of regular appointments with a physician. The presented results highlight critical aspects to be considered during treatment.
简要回顾现有的格雷夫斯病用药剂量指南。这促使我们通过极限环稳定性分析推导出推荐策略和性能评估。为此,将现有的数学治疗模型简化,纳入医学方面。从应用的角度来看,这与次优治疗有关,次优治疗可以通过比例控制器与闭环模型的时间离散化相结合来近似,以纳入与医生定期预约的影响。提出的结果强调了治疗过程中需要考虑的关键方面。
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引用次数: 0
System Identification with SINDy Neural Networks for Transistor Modeling 利用 SINDy 神经网络对晶体管建模进行系统识别
Q3 Engineering Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.073
Martin Steiger , Hans-Georg Brachtendorf
Accurate models of semiconductor devices are a key component in modern circuit development. Although parameters of such models are often derived from fundamental physical laws, device geometry or material properties, empirical models from extensive measurements have become increasingly popular. Sparse identification of non-linear dynamics (SINDy) is one approach that emphasizes interpretability. Although several extensions have been developed for this procedure, it still lacks the ability to accommodate function compositions that are very common amongst established semiconductor models. This work introduces an approach fusing the capabilities of neural networks with the core principles of SINDy to address this shortcoming. The results are compared to well-known bipolar transistor models such as Gummel-Poon and indicate promising approximation capabilities.
半导体器件的精确模型是现代电路发展的关键组成部分。虽然这类模型的参数通常来源于基本的物理定律、器件几何或材料特性,但基于广泛测量的经验模型已经越来越受欢迎。非线性动力学的稀疏识别(SINDy)是一种强调可解释性的方法。虽然已经为这个过程开发了几个扩展,但它仍然缺乏适应在已建立的半导体模型中非常常见的功能组合的能力。这项工作介绍了一种融合神经网络能力和SINDy核心原理的方法来解决这一缺点。结果与众所周知的双极晶体管模型(如Gummel-Poon)进行了比较,表明有希望的近似能力。
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引用次数: 0
Performance Space-Based ADC Development 基于空间的高性能ADC开发
Q3 Engineering Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.071
Benedikt Ohse , Jürgen Kampe , Christopher Schneider
Performance spaces represent the full range of attainable performances of an integrated analog circuit, including gain and bandwidth. Based on the knowledge of the optimal and least favorable values, simplified simulation models can be employed to optimize the system design process. We present a modified variant of the well-established Normal-Boundary Intersection method, which is used to approximate five-dimensional performance spaces in reasonable time. Based on these approximations, we develop a concept for implementing a system-level simulation that is used to design an operational transconductance amplifier for an analog-to-digital converter to improve its sampling rate. To demonstrate the usability of our concept, we perform several numerical experiments and visualize the data in parallel coordinates plots for better user comprehension.
性能空间表示集成模拟电路的全部可实现性能,包括增益和带宽。基于最优和最不利值的知识,可以采用简化的仿真模型来优化系统设计过程。我们提出了一种完善的法向边界相交方法的改进变体,该方法用于在合理的时间内近似五维性能空间。基于这些近似,我们开发了一个实现系统级仿真的概念,用于设计用于模数转换器的可操作跨导放大器,以提高其采样率。为了证明我们的概念的可用性,我们进行了几个数值实验,并在并行坐标图中可视化数据,以便更好地用户理解。
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引用次数: 0
Mathematical Modeling of Photosynthetic Eukaryotic Microorganisms Using Metabolic Networks 利用代谢网络建立光合作用真核微生物的数学模型
Q3 Engineering Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.068
M. Maton , A. Vande Wouwer
Metabolic modeling is a powerful tool for understanding microbial metabolism and is particularly appealing to a wide range of applications, from biotechnology and medicine to environmental science and sustainability. In that context, the elaboration of metabolic networks is essential despite the challenges underlying their reconstruction. While the development of genome-scale networks is computationally costly, small networks are often oversimplified, limiting their use in industrial applications. For this purpose, this paper suggests a method to identify metabolic networks of intermediate size by combining biological knowledge and a series of constraint-based methods in an iterative strategy allowing the refinement of the network definition. The present study focuses on the mathematical modeling of photosynthetic eukaryotic organisms and leads to a detailed network including energy aspects such as the proton motive force. The procedure is effective, yielding promising results while metabolic analyses provide consistent predictive capabilities of the network, in concordance with existing studies.
代谢建模是理解微生物代谢的有力工具,特别具有广泛的应用吸引力,从生物技术和医学到环境科学和可持续性。在这种情况下,代谢网络的阐述是必不可少的,尽管它们的重建面临着挑战。虽然基因组规模网络的开发在计算上是昂贵的,但小型网络往往过于简化,限制了它们在工业应用中的使用。为此,本文提出了一种识别中等规模代谢网络的方法,该方法将生物学知识和一系列基于约束的方法结合起来,采用迭代策略,允许对网络定义进行细化。本研究的重点是光合真核生物的数学建模,并导致一个详细的网络,包括能量方面,如质子动力。该程序是有效的,产生了有希望的结果,而代谢分析提供了一致的网络预测能力,与现有研究一致。
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引用次数: 0
Macroscopic Modeling and Simulation-Based Investigation of Epidemics Transport Dynamics in the Presence of Ventilation⁎ 通风条件下流行病传播动力学的宏观建模与仿真研究
Q3 Engineering Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.061
Anargiros I. Delis , Nikolaos Bekiaris-Liberis
We demonstrate the epidemics transport effect in closed spaces, performing different numerical experiments via development of a coupled, macroscopic partial differential equation (PDE) model of crowd flow, epidemics spreading dynamics, and ventilation air flow dynamics. We present numerical approximations for the coupled model with which we perform different numerical tests. In particular, we study the effect of different ventilation rates in epidemics transport (in time and space), also quantifying the infection risk via computing the total number of exposed individuals (in time and space), predicted by the model. We then discuss how the model used and the numerical results obtained could be utilized, in certain scenarios, for design of epidemics transport control strategies via manipulation of the ventilation air-flow field.
我们通过建立一个耦合的宏观偏微分方程(PDE)人群流动、流行病传播动力学和通风空气流动动力学模型,进行不同的数值实验,证明了流行病在封闭空间中的传递效应。我们给出了耦合模型的数值近似,我们用它进行了不同的数值试验。特别是,我们研究了不同通风率在流行病运输中的影响(在时间和空间上),并通过计算模型预测的暴露个体总数(在时间和空间上)来量化感染风险。然后,我们讨论了如何使用该模型以及在某些情况下如何利用所获得的数值结果,通过操纵通风气流场来设计流行病传播控制策略。
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引用次数: 0
Output controllability of large-scale nonlinear dynamical systems: analysis, computation and examples 大型非线性动力系统的输出可控性:分析、计算与实例
Q3 Engineering Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.079
L.G. van Willigenburg , J.D. Stigter
A sensitivity-based algorithm to establish state controllability is extended to establish output controllability being the ability to control the outputs of a nonlinear dynamical system instead of the full state. Due to the exceptional efficiency of the sensitivity-based algorithm, large-scale nonlinear dynamical systems can be handled, as demonstrated by several examples in this paper. As a final contribution, this paper starts with a simple analysis of state and output controllability properties of nonlinear dynamical systems in terms of connectivity’s and sensitivities. The latter relate directly to the sensitivity-based algorithm.
将基于灵敏度的建立状态可控性的算法扩展到建立输出可控性,即控制非线性动力系统输出的能力,而不是控制整个系统的状态。由于基于灵敏度的算法的卓越效率,可以处理大规模的非线性动力系统,本文的几个例子证明了这一点。作为最后的贡献,本文首先从连通性和灵敏度的角度简单分析了非线性动力系统的状态和输出可控性。后者与基于灵敏度的算法直接相关。
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引用次数: 0
Multi-Fidelity Surrogate Model for Representing Hierarchical and Conflicting Databases to Approximate Human-Seat Interaction⁎ 表示层次和冲突数据库以近似人座交互的多保真代理模型
Q3 Engineering Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.058
Gia Huy Mike Huynh , Niklas Fahse , Jonas Kneifl , Joachim Linn , Jörg Fehr
It has been shown that working with databases from heterogeneous sources of varying fidelity can be leveraged in multi-fidelity surrogate models to enhance the high-fidelity prediction accuracy or, equivalently, to reduce the amount of high-fidelity data and thus computational effort required while maintaining accuracy. In contrast, this contribution leverages low-fidelity data queried on a larger feature space to realize data-driven multi-fidelity surrogate models with a fallback option in regimes where high-fidelity data is unavailable. Accordingly, methodologies are introduced to fulfill this task and effectively resolve the contradictions, that inherently arise in multi-fidelity databases. In particular, the databases considered in this contribution feature two levels of fidelity with a defined hierarchy, where data from a high-fidelity source is, when available, prioritized over low-fidelity data. The proposed surrogate model architectures are illustrated first with a toy problem and further examined in the context of an engineering use case in autonomous driving, where the human-seat interaction is evaluated using a data-driven surrogate model, that is trained through an active learning approach. It is shown, that two proposed architectures achieve an improvement in accuracy on high-fidelity data while simultaneously performing well where high-fidelity data is unavailable compared to a naive approach.
研究表明,使用来自不同保真度的异构数据源的数据库可以在多保真度代理模型中加以利用,以提高高保真度预测精度,或者,等效地,减少高保真度数据的数量,从而在保持准确性的同时减少所需的计算工作量。相比之下,该贡献利用在更大的特征空间上查询的低保真度数据来实现数据驱动的多保真度代理模型,并在高保真度数据不可用的情况下提供回退选项。因此,本文引入了一些方法来完成这一任务,并有效地解决了多保真度数据库中固有的矛盾。特别是,本文中考虑的数据库具有两个级别的保真度,具有已定义的层次结构,其中来自高保真度源的数据在可用时优先于低保真度数据。提出的代理模型架构首先通过一个玩具问题进行说明,并在自动驾驶的工程用例背景下进一步检查,其中使用数据驱动的代理模型评估人与座椅的交互,该模型通过主动学习方法进行训练。结果表明,与朴素的方法相比,两种提出的架构在高保真数据上实现了精度的提高,同时在高保真数据不可用的情况下表现良好。
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引用次数: 0
Sensitivity Analysis of a Mathematical Model Representing the Female Endocrine Cycle 女性内分泌周期数学模型的敏感性分析
Q3 Engineering Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.044
Clara Horvath , Marie-Sophie Kohlmayer , Andreas Körner
This paper presents an extensive global sensitivity analysis of a mathematical model describing the female endocrine cycle. The model, based on a system of differential equations, captures the dynamics of Luteinizing Hormone, Follicle-Stimulating Hormone, Estrogen, and Progesterone, along with their regulatory feedback mechanisms. We employed three complementary methods – Latin Hypercube Sampling, Partial Rank Correlation Coefficient, and extended Fourier Amplitude Sensitivity Test – to analyze both linear and non-linear parameter-output relationships. The extended Fourier Amplitude Sensitivity Test method, in particular, revealed non-monotonic and non-linear interactions between input and output, highlighting the complexity of the hypothalamus-pituitary-ovary axis. Our findings offer significant insights for future model refinement and pave mathematical ways towards better understanding of the female endocrine cycle and potential clinical applications, especially in the diagnosis and treatment of reproductive disorders.
本文提出了一个广泛的全局敏感性分析的数学模型描述女性内分泌周期。该模型基于一个微分方程系统,捕捉了促黄体生成素、促卵泡激素、雌激素和孕激素的动态,以及它们的调节反馈机制。我们采用了三种互补的方法——拉丁超立方采样、偏秩相关系数和扩展傅立叶振幅灵敏度测试——来分析线性和非线性参数-输出关系。特别是扩展傅立叶振幅灵敏度测试方法,揭示了输入和输出之间的非单调和非线性相互作用,突出了下丘脑-垂体-卵巢轴的复杂性。我们的研究结果为未来的模型改进提供了重要的见解,并为更好地理解女性内分泌周期和潜在的临床应用铺平了数学途径,特别是在生殖疾病的诊断和治疗方面。
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引用次数: 0
Nonlinear Coupled PDE-ODE Model of a Distributed Ćuk Converter 分布式Ćuk转换器的非线性耦合PDE-ODE模型
Q3 Engineering Pub Date : 2025-01-01 DOI: 10.1016/j.ifacol.2025.03.017
Klaus Röbenack , Daniel Gerbet
The Ćuk converter is a particularly interesting converter, as it can be used to generate voltages which could be above or below the supply voltage. The chokes take up the most space when setting up such a converter. In this article, the chokes are replaced by transmission lines. This approach leads to a new converter topology and other mathematical models. The new distributed converter model can later on be discretized for a physical implementation to replace the two large inductances with numerous smaller inductances as suggested by Sander (2012).
Ćuk 转换器是一种特别有趣的转换器,因为它可以用来产生高于或低于电源电压的电压。在安装这种转换器时,扼流圈占用的空间最大。在本文中,扼流圈被传输线取代。这种方法带来了一种新的变流器拓扑结构和其他数学模型。新的分布式转换器模型可在以后的物理实施中进行离散化,以 Sander(2012 年)提出的众多较小电感取代两个大电感。
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引用次数: 0
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IFAC-PapersOnLine
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