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  • 101
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    Modelling altered signalling of G-protein coupled receptors in inflamed environment to advance drug design (2021)
    Details
    Publication Date: 2024-02-09
    Description: Initiated by mathematical modelling of extracellular interactions between G-protein coupled receptors (GPCRs) and ligands in normal versus diseased (inflamed) environments, we previously reported the successful design, synthesis and testing of the prototype opioid painkiller NFEPP that does not elicit adverse side effects. Uniquely, this design recognised that GPCRs function differently under pathological versus healthy conditions. We now present a novel stochastic model of GPCR function that includes intracellular dissociation of G-protein subunits and modulation of plasma membrane calcium channels associated with parameters of inflamed tissue (pH, radicals). By means of molecular dynamics simulations, we also assessed qualitative changes of the reaction rates due to additional disulfide bridges inside the GPCR binding pocket and used these rates for stochastic simulations of the corresponding reaction jump process. The modelling results were validated with in vitro experiments measuring calcium currents and G-protein activation. We found markedly reduced G-protein dissociation and calcium channel inhibition induced by NFEPP at normal pH, and enhanced constitutive G-protein activation but lower probability of ligand binding with increasing radical concentrations. These results suggest that, compared to radicals, low pH is a more important determinant of overall GPCR function in an inflamed environment. Future drug design efforts should take this into account.
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
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  • 102
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    The maximum diversity assortment selection problem (2021)
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    Publication Date: 2024-03-06
    Description: In this article, we introduce the Maximum Diversity Assortment Selection Problem (MDASP), which is a generalization of the two-dimensional Knapsack Problem (2D-KP). Given a set of rectangles and a rectangular container, the goal of 2D-KP is to determine a subset of rectangles that can be placed in the container without overlapping, i.e., a feasible assortment, such that a maximum area is covered. MDASP is to determine a set of feasible assortments, each of them covering a certain minimum threshold of the container, such that the diversity among them is maximized. Thereby, diversity is defined as the minimum or average normalized Hamming distance of all assortment pairs. MDASP was the topic of the 11th AIMMS-MOPTA Competition in 2019. The methods described in this article and the resulting computational results won the contest. In the following, we give a definition of the problem, introduce a mathematical model and solution approaches, determine upper bounds on the diversity, and conclude with computational experiments conducted on test instances derived from the 2D-KP literature.
    Language: English
    Type: article , doc-type:article
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  • 103
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    Simulation data: Data-driven model reduction of agent-based systems using the Koopman generator (2021)
    Details
    Publication Date: 2024-03-18
    Language: English
    Type: researchdata , doc-type:ResearchData
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  • 104
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    cmdtools (2021)
    Details
    Publication Date: 2024-03-18
    Description: Python implementation of severals tools (PCCA, AJC, SQRA, P/Q estimation) for the analysis of dynamical systems from the transfer operator perspective.
    Language: English
    Type: software , doc-type:Other
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  • 105
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    Data-driven model reduction of agent-based systems using the Koopman generator (2021)
    Details
    Publication Date: 2024-03-18
    Description: The dynamical behavior of social systems can be described by agent-based models. Although single agents follow easily explainable rules, complex time-evolving patterns emerge due to their interaction. The simulation and analysis of such agent-based models, however, is often prohibitively time-consuming if the number of agents is large. In this paper, we show how Koopman operator theory can be used to derive reduced models of agent-based systems using only simulation or real-world data. Our goal is to learn coarse-grained models and to represent the reduced dynamics by ordinary or stochastic differential equations. The new variables are, for instance, aggregated state variables of the agent-based model, modeling the collective behavior of larger groups or the entire population. Using benchmark problems with known coarse-grained models, we demonstrate that the obtained reduced systems are in good agreement with the analytical results, provided that the numbers of agents is sufficiently large.
    Language: English
    Type: article , doc-type:article
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  • 106
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    Agent-based modeling: Population limits and large timescales (2021)
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    Publication Date: 2024-03-18
    Description: Modeling, simulation and analysis of interacting agent systems is a broad field of research, with existing approaches reaching from informal descriptions of interaction dynamics to more formal, mathematical models. In this paper, we study agent-based models (ABMs) given as continuous-time stochastic processes and their pathwise approximation by ordinary and stochastic differential equations (ODEs and SDEs, respectively) for medium to large populations. By means of an appropriately adapted transfer operator approach we study the behavior of the ABM process on long time scales. We show that, under certain conditions, the transfer operator approach allows to bridge the gap between the pathwise results for large populations on finite timescales, i.e., the SDE limit model, and approaches built to study dynamical behavior on long time scales like large deviation theory. The latter provides a rigorous analysis of rare events including the associated asymptotic rates on timescales that scale exponentially with the population size. We demonstrate that it is possible to reveal metastable structures and timescales of rare events of the ABM process by finite-length trajectories of the SDE process for large enough populations. This approach has the potential to drastically reduce computational effort for the analysis of ABMs.
    Language: English
    Type: article , doc-type:article
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  • 107
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    Combining XOR and Partner Checkpointing for Resilient Multilevel Checkpoint/Restart (2021)
    Details
    Publication Date: 2024-04-05
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 108
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    Registration-based Tracking of Regions Defined by Level Sets of Time-dependent Scalar Fields (2021)
    Details
    Publication Date: 2024-04-05
    Description: This thesis is concerned with the wide field of feature tracking in time-dependent data. Many solutions already exist for the tracking of various features in scalar fields that are given as discrete time steps. In the field of meteorology, recently published precipitation data of the COSMO-REA2 reanalysis system gave rise to the analysis of precipitation at a convective scale for which a tracking of precipitation cells over time is desired. A previous study indicated that a tracking based on the widely used overlap criterion does not perform well for the reanalysis data. Based on a novel set of requirements, a new approach to the tracking of regions in time-dependent scalar fields is developed in the course of this thesis and applied in a prototypical study to example datasets of the COSMO-REA2 system. Despite the concrete motivation of using the developed method for subsequent studies of precipitation, the tracking approach is designed to be applicable for arbitrary scalar quantities that can conceptually be given on uniform grids of arbitrary dimensions. Based on a detailed description of the utilized methods, this thesis presents a novel tracking solution whose correspondence identification is based on image registration of successive time steps in combination with a hierarchical watershed segmentation by means of which features are extracted. The proposed implementation allows for an efficient generation of tracking results under the premise that the registration-based correspondence information has been precomputed.
    Language: English
    Type: masterthesis , doc-type:masterThesis
    Format: application/pdf
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  • 109
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    On the Regression Model for Generalized Normal Distributions (2021)
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    Publication Date: 2024-04-26
    Description: The traditional linear regression model that assumes normal residuals is applied extensively in engineering and science. However, the normality assumption of the model residuals is often ineffective. This drawback can be overcome by using a generalized normal regression model that assumes a non-normal response. In this paper, we propose regression models based on generalizations of the normal distribution. The proposed regression models can be used effectively in modeling data with a highly skewed response. Furthermore, we study in some details the structural properties of the proposed generalizations of the normal distribution. The maximum likelihood method is used for estimating the parameters of the proposed method. The performance of the maximum likelihood estimators in estimating the distributional parameters is assessed through a small simulation study. Applications to two real datasets are given to illustrate the flexibility and the usefulness of the proposed distributions and their regression models.
    Language: English
    Type: article , doc-type:article
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  • 110
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    Controlling transient gas flow in real-world pipeline intersection areas (2021)
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    Publication Date: 2024-04-26
    Description: Compressor stations are the heart of every high-pressure gas transport network. Located at intersection areas of the network they are contained in huge complex plants, where they are in combination with valves and regulators responsible for routing and pushing the gas through the network. Due to their complexity and lack of data compressor stations are usually dealt with in the scientific literature in a highly simplified and idealized manner. As part of an ongoing project with one of Germany's largest Transmission System Operators to develop a decision support system for their dispatching center, we investigated how to automatize control of compressor stations. Each station has to be in a particular configuration, leading in combination with the other nearby elements to a discrete set of up to 2000 possible feasible operation modes in the intersection area. Since the desired performance of the station changes over time, the configuration of the station has to adapt. Our goal is to minimize the necessary changes in the overall operation modes and related elements over time, while fulfilling a preset performance envelope or demand scenario. This article describes the chosen model and the implemented mixed integer programming based algorithms to tackle this challenge. By presenting extensive computational results on real world data we demonstrate the performance of our approach.
    Language: English
    Type: article , doc-type:article
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  • 111
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    Distribution System Planning with Battery Storage using Multiperiod Optimal Power Flow (2021)
    Details
    Publication Date: 2024-04-26
    Description: The ongoing energy transition introduces new challenges for distribution networks and brings about the need to expand existing power grid capacities. In order to contain network expansion and with it economic costs, utilization of various flexibility options to reduce expansion needs is discussed. This paper proposes a multiperiod optimal power flow (MPOPF) approach with a new continuous network expansion formulation to optimize the deployment of flexibility options under the objective of minimizing network expansion costs. In a comparison of the newly proposed continuous network expansion formulation with an existing mixed integer formulation and a continuous interpretation of the latter the here proposed formulation is shown to be useful in order to obtain a solvable problem and contain computational efforts. The presented MPOPF including the flexibility options storage units and curtailment is then assessed on synthetic medium voltage grids and applied to evaluate the benefit of a combined vs. a stepwise optimization of these flexibility options. It is demonstrated that using a local solver the proposed approach is applicable and yields a solution in reasonable time. Furthermore, it is shown that the combined optimization generally leads to a more efficient utilization of the considered flexibility options and therefore lower grid expansion costs than the stepwise consideration.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 112
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    Modeling and forecasting gas network flows with multivariate time series and mathematical programming approach (2021)
    Details
    Publication Date: 2024-04-26
    Description: With annual consumption of approx. 95 billion cubic me-ters and similar amounts of gas just transshipped through Germany toother EU states, Germany’s gas transport system plays a vital role inEuropean energy supply. The complex, more than 40,000 km long high-pressure transmission network is controlled by several transmission sys-tem operators (TSOs) whose main task is to provide security of supplyin a cost-efficient way. Given the slow speed of gas flows through the gastransmission network pipelines, it has been an essential task for the gasnetwork operators to enhance the forecast tools to build an accurate andeffective gas flow prediction model for the whole network. By incorpo-rating the recent progress in mathematical programming and time seriesmodeling, we aim to model natural gas network and predict gas in- andout-flows at multiple supply and demand nodes for different forecastinghorizons. Our model is able to describe the dynamics in the network bydetecting the key nodes, which may help to build an optimal manage-ment strategy for transmission system operators.
    Language: English
    Type: reportzib , doc-type:preprint
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  • 113
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    Deep learning for spatio-temporal supply anddemand forecasting in natural gas transmission networks (2021)
    Details
    Publication Date: 2024-04-26
    Description: Germany is the largest market for natural gas in the European Union, with an annual consumption of approx. 95 billion cubic meters. Germany's high-pressure gas pipeline network is roughly 40,000 km long, which enables highly fluctuating quantities of gas to be transported safely over long distances. Considering that similar amounts of gas are also transshipped through Germany to other EU states, it is clear that Germany's gas transport system is essential to the European energy supply. Since the average velocity of gas in a pipeline is only 25km/h, an adequate high-precision, high-frequency forecasting of supply and demand is crucial for efficient control and operation of such a transmission network. We propose a deep learning model based on spatio-temporal convolutional neural networks (DLST) to tackle the problem of gas flow forecasting in a complex high-pressure transmission network. Experiments show that our model effectively captures comprehensive spatio-temporal correlations through modeling gas networks and consistently outperforms state-of-the-art benchmarks on real-world data sets by at least 21%. The results demonstrate that the proposed model can deal with complex nonlinear gas network flow forecasting with high accuracy and effectiveness.
    Language: English
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  • 114
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    Deep learning for spatio-temporal supply and demand forecasting in natural gas transmission networks (2021)
    Details
    Publication Date: 2024-04-26
    Description: Germany is the largest market for natural gas in the European Union, with an annual consumption of approx. 95 billion cubic meters. Germany's high-pressure gas pipeline network is roughly 40,000 km long, which enables highly fluctuating quantities of gas to be transported safely over long distances. Considering that similar amounts of gas are also transshipped through Germany to other EU states, it is clear that Germany's gas transport system is essential to the European energy supply. Since the average velocity of gas in a pipeline is only 25km/h, an adequate high-precision, high-frequency forecasting of supply and demand is crucial for efficient control and operation of such a transmission network. We propose a deep learning model based on spatio-temporal convolutional neural networks (DLST) to tackle the problem of gas flow forecasting in a complex high-pressure transmission network. Experiments show that our model effectively captures comprehensive spatio-temporal correlations through modeling gas networks and consistently outperforms state-of-the-art benchmarks on real-world data sets by at least 21$\%$. The results demonstrate that the proposed model can deal with complex nonlinear gas network flow forecasting with high accuracy and effectiveness.
    Language: English
    Type: reportzib , doc-type:preprint
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  • 115
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    A hierarchical optimization approach to robust design of energy supply systems based on a mixed-integer linear model (2021)
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    Publication Date: 2024-04-26
    Description: In designing energy supply systems, designers should heighten the robustness in performance criteria against the uncertainty in energy demands. In this paper, a robust optimal design method using a hierarchical mixed-integer linear programming (MILP) method is proposed to maximize the robustness of energy supply systems under uncertain energy demands based on a mixed-integer linear model. A robust optimal design problem is formulated as a three-level min-max-min MILP one by expressing uncertain energy demands by intervals, evaluating the robustness in a performance criterion based on the minimax regret criterion, and considering relationships among integer design variables, uncertain energy demands, and integer and continuous operation variables. This problem is solved by evaluating upper and lower bounds for the minimum of the maximum regret of the performance criterion repeatedly outside, and evaluating lower and upper bounds for the maximum regret repeatedly inside. Different types of optimization problems are solved by applying a hierarchical MILP method developed for ordinary optimal design problems without and with its modifications. In a case study, the proposed approach is applied to the robust optimal design of a cogeneration system. Through the study, its validity and effectiveness are ascertained, and some features of the obtained robust designs are clarified.
    Language: English
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  • 116
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    Robust Approximation of Chance Constrained DC Optimal Power Flow under Decision-Dependent Uncertainty (2021)
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    Publication Date: 2024-04-26
    Description: We propose a mathematical optimization model and its solution for joint chance constrained DC Optimal Power Flow. In this application, it is particularly important that there is a high probability of transmission limits being satisfied, even in the case of uncertain or fluctuating feed-in from renewable energy sources. In critical network situations where the network risks overload, renewable energy feed-in has to be curtailed by the transmission system operator (TSO). The TSO can reduce the feed-in in discrete steps at each network node. The proposed optimization model minimizes curtailment while ensuring that there is a high probability of transmission limits being maintained. The latter is modeled via (joint) chance constraints that are computationally challenging. Thus, we propose a solution approach based on the robust safe approximation of these constraints. Hereby, probabilistic constraints are replaced by robust constraints with suitably defined uncertainty sets constructed from historical data. The ability to discretely control the power feed-in then leads to a robust optimization problem with decision-dependent uncertainties, i.e. the uncertainty sets depend on decision variables. We propose an equivalent mixed-integer linear reformulation for box uncertainties with the exact linearization of bilinear terms. Finally, we present numerical results for different test cases from the Nesta archive, as well as for a real network. We consider the discrete curtailment of solar feed-in, for which we use real-world weather and network data. The experimental tests demonstrate the effectiveness of this method and run times are very fast. Moreover, on average the calculated robust solutions only lead to a small increase in curtailment, when compared to nominal solutions.
    Language: English
    Type: article , doc-type:article
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  • 117
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    Effect of model reduction by time aggregation in multiobjective optimal design of energy supply systems by a hierarchical MILP method (2021)
    Details
    Publication Date: 2024-04-26
    Description: The mixed-integer linear programming (MILP) method has been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. In addition, a method of reducing model by time aggregation has been proposed to search design candidates accurately and efficiently at the upper level. In this paper, the hierarchical MILP method and model reduction by time aggregation are applied to the multiobjective optimal design. The methods of clustering periods by the order of time series, by the k-medoids method, and based on an operational strategy are applied for the model reduction. As a case study, the multiobjective optimal design of a gas turbine cogeneration system is investigated by adopting the annual total cost and primary energy consumption as the objective functions, and the clustering methods are compared with one another in terms of the computation efficiency. It turns out that the model reduction by any clustering method is effective to enhance the computation efficiency when importance is given to minimizing the first objective function, but that the model reduction only by the k-medoids method is effective very limitedly when importance is given to minimizing the second objective function.
    Language: English
    Type: article , doc-type:article
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  • 118
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    Modeling functional time series and mixed-type predictors with partially functional autoregressions* (2021)
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    Publication Date: 2024-04-26
    Description: In many business and economics studies, researchers have sought to measure the dynamic dependence of curves with high-dimensional mixed-type predictors. We propose a partially functional autoregressive model (pFAR) where the serial dependence of curves is controlled by coefficient operators that are defined on a two-dimensional surface, and the individual and group effects of mixed-type predictors are estimated with a two-layer regularization. We develop an efficient estimation with the proven asymptotic properties of consistency and sparsity. We show how to choose the sieve and tuning parameters in regularization based on a forward-looking criterion. In addition to the asymptotic properties, numerical validation suggests that the dependence structure is accurately detected. The implementation of the pFAR within a real-world analysis of dependence in German daily natural gas flow curves, with seven lagged curves and 85 scalar predictors, produces superior forecast accuracy and an insightful understanding of the dynamics of natural gas supply and demand for the municipal, industry, and border nodes, respectively.
    Language: English
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  • 119
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    Optimization of Stationary Expansion Planning and Transient Network Control by Mixed-Integer Nonlinear Programming (2021)
    Details
    Publication Date: 2024-04-26
    Language: English
    Type: doctoralthesis , doc-type:doctoralThesis
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  • 120
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    Statistical analysis and modeling for detecting regime changes in gas nomination time series (2021)
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    Publication Date: 2024-04-26
    Description: As a result of the legislation for gas markets introduced by the European Union in 2005, separate independent companies have to conduct the transport and trading of natural gas. The current gas market of Germany, which has a market value of more than 54 billion USD, consists of Transmission System Operators (TSO), network users, and traders. Traders can nominate a certain amount of gas anytime and anywhere in the network. Such unrestricted access for the traders, on the other hand, increase the uncertainty in the gas supply management. Some customers’ behaviors may cause abrupt structural changes in gas flow time series. In particular, it is a challenging task for the TSO operators to predict gas nominations 6 to 10 hours ahead. In our study, we aim to investigate the regime changes in the time series of nominations to predict the 6 to 10 hours ahead of gas nominations.
    Language: English
    Type: reportzib , doc-type:preprint
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  • 121
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    CMAP-LAP: Configurable Massively Parallel Solver for Lattice Problems (2021)
    Details
    Publication Date: 2024-04-26
    Description: Lattice problems are a class of optimization problems that are notably hard. There are no classical or quantum algorithms known to solve these problems efficiently. Their hardness has made lattices a major cryptographic primitive for post-quantum cryptography. Several different approaches have been used for lattice problems with different computational profiles; some suffer from super-exponential time, and others require exponential space. This motivated us to develop a novel lattice problem solver, CMAP-LAP, based on the clever coordination of different algorithms that run massively in parallel. With our flexible framework, heterogeneous modules run asynchronously in parallel on a large-scale distributed system while exchanging information, which drastically boosts the overall performance. We also implement full checkpoint-and-restart functionality, which is vital to high-dimensional lattice problems. Through numerical experiments with up to 103,680 cores, we evaluated the performance and stability of our system and demonstrated its high capability for future massive-scale experiments.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 122
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    CMAP-LAP: Configurable Massively Parallel Solver for Lattice Problems (2021)
    Details
    Publication Date: 2024-04-26
    Description: Lattice problems are a class of optimization problems that are notably hard. There are no classical or quantum algorithms known to solve these problems efficiently. Their hardness has made lattices a major cryptographic primitive for post-quantum cryptography. Several different approaches have been used for lattice problems with different computational profiles; some suffer from super-exponential time, and others require exponential space. This motivated us to develop a novel lattice problem solver, CMAP-LAP, based on the clever coordination of different algorithms that run massively in parallel. With our flexible framework, heterogeneous modules run asynchronously in parallel on a large-scale distributed system while exchanging information, which drastically boosts the overall performance. We also implement full checkpoint-and-restart functionality, which is vital to high-dimensional lattice problems. Through numerical experiments with up to 103,680 cores, we evaluated the performance and stability of our system and demonstrated its high capability for future massive-scale experiments.
    Language: English
    Type: reportzib , doc-type:preprint
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  • 123
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    Blending hydrogen into natural gas: An assessment of the capacity of the German gas grid; Technical Report (2021)
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    Publication Date: 2024-04-26
    Description: In the transition towards a pure hydrogen infrastructure, utilizing the existing natural gas infrastructure is a necessity. In this study, the maximal technically feasible injection of hydrogen into the existing German natural gas transmission network is analysed with respect to regulatory limits regarding the gas quality. We propose a transient tracking model based on the general pooling problem including linepack. The analysis is conducted using real-world hourly gas flow data on a network of about 10,000 km length.
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  • 124
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    Massively parallel sharing lattice basis reduction (2021)
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    Publication Date: 2024-04-26
    Description: For cryptanalysis in lattice-based schemes, the performance evaluation of lattice basis reduction using high-performance computers is becoming increasingly important for the determination of the security level. We propose a distributed and asynchronous parallel reduction algorithm based on randomization and DeepBKZ, which is an improved variant of the block Korkine-Zolotarev (BKZ) reduction algorithm. Randomized copies of a lattice basis are distributed to up to 103,680 cores and independently reduced in parallel, while some basis vectors are shared asynchronously among all processes via MPI. There is a trade-off between randomization and information sharing; if a substantial amount of information is shared, all processes will work on the same problem, thereby diminishing the benefit of parallelization. To monitor this balance between randomness and sharing, we propose a metric to quantify the variety of lattice bases. We empirically find an optimal parameter of sharing for high-dimensional lattices. We demonstrate the efficacy of our proposed parallel algorithm and implementation with respect to both performance and scalability through our experiments.
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  • 125
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    Interface stability of compressible fluids in porous media (2021)
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    Publication Date: 2024-04-26
    Description: The stability of flows in porous media plays a vital role in transiting energy supply from natural gas to hydrogen, especially for estimating the usability of existing underground gas storage infrastructures. Thus, this research aims to analyze the interface stability of the tangential-velocity discontinuity between two compressible gases by using Darcy's model to include the porosity effect. The results shown in this research will be a basis for considering whether underground gas storages in porous material can be used to store hydrogen. We show the relation between the Mach number M, the viscosity \mu, and the porosity \epsilon on the stability of the interface. This interface stability affects gases' withdrawal and injection processes, thus will help us to determine the velocity which with gas can be extracted and injected into the storage effectively. By imposing solid walls along the flow direction, the critical values of these parameters regarding the stability of the interface are smaller than when considering no walls. The consideration of bounded flows approaches the problem more realistically. In particular, this analysis plays a vital role when considering two-dimensional gas flows in storages and pipes.
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  • 126
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    Effect of water depth on Kelvin - Helmholtz instability in a shallow-water flow (2021)
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    Publication Date: 2024-04-26
    Description: It is well known that the interface between two regions of an incompressible ideal fluid flow moving in a relative motion is necessarily destabilized, regardless of the velocity difference's strength. This phenomenon is the so-called Kelvin-Helmholtz instability (KHI). However, a large number of works demonstrated a surprising result that the instability is suppressed for shallow water flows; the interface is stabilized if the Froude number, defined by the velocity difference's ratio to the gravity wave's speed, is sufficiently large. In a limited way, these authors have been used the shallow-water equations without the higher-order effect of the dispersive terms. Thus, this investigation aims to examine these higher-order dispersive effects to analyze the interface stability problem of tangential-velocity discontinuity in shallow-water flows. In particular, we use the Green-Naghdi equations to introduce the dispersive terms related to the depth and the depth-averaged horizontal velocities of the fluid. We show that the interface stability depends on the Froude number (i.e., the velocity difference's strength) and the water depth. A critical value of the Froude number to stabilize the interface is smaller than the case of no dispersive terms, and the flow in a deeper region is more stable than in a shallower one. We also consider the distribution of kinetic and potential energy to clarify a feature characteristic of a large class of instabilities in shallow water flow. The instability of flows is caused by the decrease in the kinetic energy during the perturbation of waves. This phenomenon is known as negative energy modes and plays a vital role in applying the model to industrial equipment. A conclusion is that the equipartition of energies occurs if and only if the velocity difference is zero and the water depth is shallow enough to ignore the dispersive terms.
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  • 127
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    Instability of a tangential discontinuity surface in a three-dimensional compressible medium (2021)
    Details
    Publication Date: 2024-04-26
    Description: Compressible flows appear in many natural and technological processes, for instance, the flow of natural gases in a pipe system. Thus, a detailed study of the stability of tangential velocity discontinuity in compressible media is relevant and necessary. The first early investigation in two-dimensional (2D) media was given more than 70 years ago. In this article, we continue investigating the stability in three-dimensional (3D) media. The idealized statement of this problem in an infinite spatial space was studied by Syrovatskii in 1954. However, the omission of the absolute sign of cos θ with θ being the angle between vectors of velocity and wave number in a certain inequality produced the inaccurate conclusion that the flow is always unstable for entire values of the Mach number M. First, we revisit this case to arrive at the correct conclusion, namely that the discontinuity surface is stabilized for a large Mach number with a given value of the angle θ. Next, we introduce a real finite spatial system such that it is bounded by solid walls along the flow direction. We show that the discontinuity surface is stable if and only if the dispersion relation equation has only real roots, with a large value of the Mach number; otherwise, the surface is always unstable. In particular, we show that a smaller critical value of the Mach number is required to make the flow in a narrow channel stable.
    Language: English
    Type: article , doc-type:article
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  • 128
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    Faster algorithms for Steiner tree and related problems: From theory to practice (2021)
    Details
    Publication Date: 2024-04-26
    Language: English
    Type: doctoralthesis , doc-type:doctoralThesis
    Format: application/pdf
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  • 129
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    Inference of historical influence networks (2021)
    Details
    Publication Date: 2024-05-16
    Description: We study the romanization process of northern Africa from 50 BC till 300 AD. Our goal is to infer the communication strength between different subregions, based on the evolution of the status of cities. Herefore, we use the general inverse infection model, that infers the weights of a known underlying network, given observations of the spreading on this network. As infection process we choose the SI metapopulation model, where I stands for a city with a Roman status. To solve the minimization problem we use the particle swarm optimization algorithm with a specific choice of parameters.
    Language: German
    Type: conferenceobject , doc-type:conferenceObject
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  • 130
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    Crashkurs BWA : betriebswirtschaftliche Auswertungen erstellen, lesen und verstehen (2021)
    Details
    Title: Crashkurs BWA : betriebswirtschaftliche Auswertungen erstellen, lesen und verstehen
    Author: Träger, Elisabeth
    Edition: 1. Auflage
    Year of publication: 2021
    Pages: 180 Seiten
    ISBN: 978-3-648-13768-0
    Type of Medium: Book
    Language: German
    URL: Inhaltstext
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  • 131
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    Book
    Crashkurs Internes Kontrollsystem für Buchhaltung und Steuern / (2021)
    Details
    Title: Crashkurs Internes Kontrollsystem für Buchhaltung und Steuern /
    Author: Alves, Winfried
    Edition: 2. völlig überarbeitete und erweiterte Auflage
    Year of publication: 2021
    Pages: 167 Seiten
    ISBN: 978-3-648-14049-9
    Type of Medium: Book
    Language: German
    URL: Inhaltstext
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  • 132
    Book
    Book
    Schwierige Geschäftsvorfälle richtig buchen / (2021)
    Freiburg im Breisgau :Haufe-Lexware,
    Details
    Title: Schwierige Geschäftsvorfälle richtig buchen /
    Author: Thomsen, Iris
    Contributer: Zöllner, Nikolaus
    Edition: 15. Auflage
    Publisher: Freiburg im Breisgau :Haufe-Lexware,
    Year of publication: 2021
    Pages: 413 Seiten
    ISBN: 978-3-648-14840-2
    Type of Medium: Book
    Language: German
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  • 133
    Book
    Book
    Erfurter Kommentar zum Arbeitsrecht (2021)
    München :C.H. Beck,
    Details
    Title: Erfurter Kommentar zum Arbeitsrecht
    Contributer: Müller-Glöge, Rudi , Preis, Ulrich , Gallner, Inken
    Edition: 22. Auflage
    Publisher: München :C.H. Beck,
    Year of publication: 2021
    Pages: 3100 Seiten
    ISBN: 978-3-406-77038-8
    Type of Medium: Book
    Language: German
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  • 134
    Book
    Book
    Introduction to Quantum Computing / (2021)
    Basel :Springer International Publishing,
    Details
    Title: Introduction to Quantum Computing /
    Author: LaPierre, Ray
    Publisher: Basel :Springer International Publishing,
    Year of publication: 2021
    Pages: 368 Seiten
    ISBN: 978-3-030-69317-6
    Type of Medium: Book
    Language: English
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  • 135
    Book
    Book
    Forschungsdatenmanagement und Recht : Datenschutz-, Urheber- und Vertragsrecht (2021)
    Feldkirch/Düns :Neugebauer,
    Details
    Title: Forschungsdatenmanagement und Recht : Datenschutz-, Urheber- und Vertragsrecht
    Author: Baumann, Paul
    Contributer: Krahn, Philipp , Lauber-Rönsberg, Anne
    Publisher: Feldkirch/Düns :Neugebauer,
    Year of publication: 2021
    Pages: 304 Seiten
    ISBN: 978-3-85376-328-5
    Type of Medium: Book
    Language: German
    URL: Inhaltsverzeichnis
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  • 136
    Book
    Book
    Git Handbuch für Einsteiger : Der leichte Weg zum Git-Experten (2021)
    Landshut :BMU Media Verlag,
    Details
    Title: Git Handbuch für Einsteiger : Der leichte Weg zum Git-Experten
    Author: Fuchs, Paul
    Publisher: Landshut :BMU Media Verlag,
    Year of publication: 2021
    Pages: 307 Seiten
    ISBN: 978-3-96645-119-2
    Type of Medium: Book
    Language: German
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  • 137
    Book
    Book
    Git für Dummies / (2021)
    Weinheim :Wiley-VCH,
    Details
    Title: Git für Dummies /
    Author: Kaufmann, Michael
    Contributer: Binkle, Harald
    Publisher: Weinheim :Wiley-VCH,
    Year of publication: 2021
    Pages: 417 Seiten
    ISBN: 978-3-527-71697-5
    Type of Medium: Book
    Language: German
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  • 138
    Book
    Book
    Handbuch Prüfung ortsveränderlicher elektrischer Geräte : Prüfabläufe, Grenz- und Richtwerte gem. DIN VDE 0701-0702 für die Prüfung vor Ort (2021)
    Forum Verlag Herkert,
    Details
    Title: Handbuch Prüfung ortsveränderlicher elektrischer Geräte : Prüfabläufe, Grenz- und Richtwerte gem. DIN VDE 0701-0702 für die Prüfung vor Ort
    Contributer: Donath, Karl [Verfasser] , Rottmann, Rainer [Verfasser] , Gavrancic, Milan [Verfasser] , Orgel, Christian [Verfasser]
    Edition: 4. überarbeitete Auflage
    Publisher: Forum Verlag Herkert,
    Year of publication: 2021
    Pages: 311 Seiten
    ISBN: 978-3-96314-615-2
    Type of Medium: Book
    Language: German
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  • 139
    Book
    Book
    Handbuch Prüfung ortsfester elektrischer Anlagen und Betriebsmittel : Prüfabläufe, Grenz- und Richtwerte gem. DIN VDE 0100-600 und 0105-100 für die Prüfung vor Ort (2021)
    Forum Verlag Herkert,
    Details
    Title: Handbuch Prüfung ortsfester elektrischer Anlagen und Betriebsmittel : Prüfabläufe, Grenz- und Richtwerte gem. DIN VDE 0100-600 und 0105-100 für die Prüfung vor Ort
    Author: Donath, Karl [Verfasser]
    Contributer: Rottmann, Rainer [Verfasser] , Orgel, Christian [Verfasser]
    Edition: 4. überarbeitete Auflage
    Publisher: Forum Verlag Herkert,
    Year of publication: 2021
    Pages: 374 Seiten
    Type of Medium: Book
    Language: German
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  • 140
    Book
    Book
    Docker : das Praxisbuch für Entwickler und DevOps-Teams (2021)
    Details
    Title: Docker : das Praxisbuch für Entwickler und DevOps-Teams
    Author: Öggl, Bernd
    Contributer: Kofler, Michael
    Edition: 3. Aufl.
    Year of publication: 2021
    Pages: 496 S. : , Illustrationen, Diagramme
    ISBN: 978-3-8362-8634-3
    Type of Medium: Book
    Language: German
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  • 141
    Book
    Book
    HTML und CSS : das umfassende Handbuch (2021)
    Bonn :Rheinwerk Verlag,
    Details
    Title: HTML und CSS : das umfassende Handbuch
    Author: Wolf, Jürgen
    Edition: 4., aktualisierte und überarbeitete Auflage
    Publisher: Bonn :Rheinwerk Verlag,
    Year of publication: 2021
    Pages: 1158 Seiten
    ISBN: 978-3-8362-8117-1
    Type of Medium: Book
    Language: German
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  • 142
    Book
    Book
    Linear Algebra : Theory, Intuition, Code (2021)
    Sincxpress Bv,
    Details
    Title: Linear Algebra : Theory, Intuition, Code
    Author: Cohen, Mike X
    Publisher: Sincxpress Bv,
    Year of publication: 2021
    Pages: 548 S.
    ISBN: 978-90-831366-0-8
    Type of Medium: Book
    Language: German
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  • 143
    Book
    Book
    Programming Rust : fast, safe systems development (2021)
    Beijing ; Boston ; Farnham ; Sebastopol :O'Reilly,
    Details
    Title: Programming Rust : fast, safe systems development
    Author: Blandy, Jim
    Contributer: Orendorff, Jason , Tindall, Leonora
    Edition: Second edition
    Publisher: Beijing ; Boston ; Farnham ; Sebastopol :O'Reilly,
    Year of publication: 2021
    Pages: xix, 711 Seiten
    ISBN: 9781492052562
    Type of Medium: Book
    Language: English
    Parallel Title: Erscheint auch als Druck-Ausgabe 978-1-492-05259-3
    URL: https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=2949563&site=ehost-live
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  • 144
    Book
    Book
    Liberating structures : Entscheidungsfindung revolutionieren (2021)
    München :Verlag Franz Vahlen GmbH,
    Details
    Title: Liberating structures : Entscheidungsfindung revolutionieren
    Author: Steinhöfer, Daniel
    Publisher: München :Verlag Franz Vahlen GmbH,
    Year of publication: 2021
    Pages: 120 Seiten
    ISBN: 978-3-8006-5929-6
    Type of Medium: Book
    Language: German
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  • 145
    Book
    Book
    Götzendämmerung : Kunst und Künstliche Intelligenz (2021)
    Bielefeld :transcript,
    Details
    Title: Götzendämmerung : Kunst und Künstliche Intelligenz
    Contributer: Dotzler, Bernhard J. , Karpat, Berkan
    Publisher: Bielefeld :transcript,
    Year of publication: 2021
    Pages: 154 Seiten
    ISBN: 978-3-8376-5976-4
    Type of Medium: Book
    Language: German
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  • 146
    Book
    Book
    Grundlagen der Eingruppierung TVöD und TV-L : das aktuelle Eingruppierungsrecht im öffentlichen Dienst (2021)
    Berlin :Walhalla und Praetoria Verlag,
    Details
    Title: Grundlagen der Eingruppierung TVöD und TV-L : das aktuelle Eingruppierungsrecht im öffentlichen Dienst
    Author: Richter, Achim
    Contributer: Gamisch, Annett , Mohr, Thomas
    Edition: 7., aktualisierte Auflage, Bearbeitungsstand: Juni 2017
    Publisher: Berlin :Walhalla und Praetoria Verlag,
    Year of publication: 2021
    Pages: 112 Seiten
    ISBN: 978-3-8029-1599-4
    Type of Medium: Book
    Language: German
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  • 147
    Book
    Book
    Muster : Theorie der digitalen Gesellschaft (2021)
    München :C.H. Beck,
    Details
    Title: Muster : Theorie der digitalen Gesellschaft
    Author: Nassehi, Armin
    Edition: 1. Auflage
    Publisher: München :C.H. Beck,
    Year of publication: 2021
    Pages: 352 Seiten
    ISBN: 978-3-406-76786-9
    Type of Medium: Book
    Language: German
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  • 148
    Book
    Book
    ¬The¬ science of science / (2021)
    Cambridge :Cambridge University Press,
    Details
    Title: ¬The¬ science of science /
    Author: Wang, Dashun
    Contributer: Barabási, Albert-László
    Publisher: Cambridge :Cambridge University Press,
    Year of publication: 2021
    Pages: x, 303 Seiten
    ISBN: 978-1-108-71695-6
    Type of Medium: Book
    Language: English
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