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Determining cost-efficient controls of electrical energy storages using dynamic programming J. Math. Industry Pub Date : 2024-02-12 Michael Stiglmayr, Svenja Uhlemeyer, Björn Uhlemeyer, Markus Zdrallek
Volatile electrical energy prices are a challenge and an opportunity for small and medium-sized companies in energy-intensive industries. By using electrical energy storage and/or an adaptation of production processes, companies can significantly profit from time-depending energy prices and reduce their energy costs. We consider a time-discrete optimal control problem to reach a desired final state
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Respiratory particles: from analytical estimates to disease transmission J. Math. Industry Pub Date : 2024-01-12 J. A. Ferreira, Paula de Oliveira, P. M. da Silva
Respiratory particles containing infectious pathogens are responsible for a large number of diseases. To define health politics and save lives, it is important to study their transmission mechanisms, namely the path of particles once expelled. This path depends on several driving factors as intrinsic properties of particles, environmental aspects and morphology of the scenario. Following physical arguments
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Crack modeling via minimum-weight surfaces in 3d Voronoi diagrams J. Math. Industry Pub Date : 2023-11-27 Christian Jung, Claudia Redenbach
As the number one building material, concrete is of fundamental importance in civil engineering. Understanding its failure mechanisms is essential for designing sustainable buildings and infrastructure. Micro-computed tomography (μCT) is a well-established tool for virtually assessing crack initiation and propagation in concrete. The reconstructed 3d images can be examined via techniques from the fields
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Increasing design flexibility by manually adapting the solution space for crashworthiness J. Math. Industry Pub Date : 2023-10-12 Paolo Ascia, Volker A. Lange, Fabian Duddeck
The solution space methodology, as presented in 2013, was meant to guide developers at the very beginning of the development process of a new mechanically crashworthy car. Several attempts were already made to use this methodology at later development stages. However, they all encountered problems related to its very strict and demanding corridors, thus constricting the design parameters. To allow
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The modelling of urban running races J. Math. Industry Pub Date : 2023-08-02 Ricardo Enguiça, Nuno D. Lopes
In this paper, we model mass running urban races, taking into consideration several conditioning factors. The main goal is to find ideal configurations of the start of the race, splitting it into several waves, reducing the density of athletes and the overall time lost, when comparing the normal race results with a race without density constraints. This model takes into account distinct realistic runners’
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Dual stochastic descriptions of streamflow dynamics under model ambiguity through a Markovian embedding J. Math. Industry Pub Date : 2023-07-25 Hidekazu Yoshioka, Yumi Yoshioka
Hamilton–Jacobi–Bellman equation (HJBE) and backward stochastic differential equation (BSDE) are the two faces of stochastic control. We explore their equivalence focusing on a system of self-exciting and affine stochastic differential equations (SDEs) arising in streamflow dynamics. Our SDE is a finite-dimensional Markovian embedding of an infinite-dimensional jump-driven process called the superposition
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Parallel-in-time optimization of induction motors J. Math. Industry Pub Date : 2023-06-22 Jens Hahne, Björn Polenz, Iryna Kulchytska-Ruchka, Stephanie Friedhoff, Stefan Ulbrich, Sebastian Schöps
Parallel-in-time (PinT) methods were developed to accelerate time-domain solution of evolutionary problems using modern parallel computer architectures. In this paper we incorporate one of the efficient PinT approaches, in particular, the asynchronous truncated multigrid-reduction-in-time algorithm, into a bound constrained optimization procedure applied to an induction machine. Calculation of an optimal
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Unsupervised deep learning techniques for automatic detection of plant diseases: reducing the need of manual labelling of plant images J. Math. Industry Pub Date : 2023-05-30 Alessandro Benfenati, Paola Causin, Roberto Oberti, Giovanni Stefanello
Crop protection from diseases through applications of plant protection products is crucial to secure worldwide food production. Nevertheless, sustainable management of plant diseases is an open challenge with a major role in the economic and environmental impact of agricultural activities. A primary contribution is expected to come from precision crop protection approaches, with treatments tailored
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An optimal control problem for single-spot pulsed laser welding J. Math. Industry Pub Date : 2023-03-16 Roland Herzog, Dmytro Strelnikov
We consider an optimal control problem for a single-spot pulsed laser welding problem. The distribution of thermal energy is described by a quasilinear heat equation. Our emphasis is on materials which tend to suffer from hot cracking when welded, such as aluminum alloys. A simple precursor for the occurrence of hot cracks is the velocity of the solidification front. We therefore formulate an optimal
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A mathematical characterization of anatomically consistent blood capillary networks J. Math. Industry Pub Date : 2023-03-02 Marina Bertolini, Paola Causin, Cristina Turrini
Blood microcirculation is the site of control of tissue perfusion, blood-tissue exchange, and tissue blood volume. Despite the many irregularities, almost ubiquitously, one can recognize in microcirculation vessels a hierarchy of arterioles and venules, organized in tree-like structures, and capillary plexi, organized in net-like structures. Whilst for arterioles and venules it may be envisageable
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Segmentation and morphological analysis of amyloid fibrils from cryo-EM image data J. Math. Industry Pub Date : 2023-02-07 Matthias Weber, Matthias Neumann, Matthias Schmidt, Peter Benedikt Pfeiffer, Akanksha Bansal, Marcus Fändrich, Volker Schmidt
Fast assessment of the composition of amyloid fibril samples from cryo-EM data poses a serious challenge to existing image analysis tools. We develop a method for automated segmentation of single fibrils requiring only little user input during the training process. This is achieved by combining a binary segmentation based on a convolutional neural network with preprocessing steps to allow for easy
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A hybrid compartmental model with a case study of COVID-19 in Great Britain and Israel J. Math. Industry Pub Date : 2023-02-03 Greta Malaspina, Stevo Racković, Filipa Valdeira
Given the severe impact of COVID-19 on several societal levels, it is of crucial importance to model the impact of restriction measures on the pandemic evolution, so that governments are able to make informed decisions. Even though there have been countless attempts to propose diverse models since the rise of the outbreak, the increase in data availability and start of vaccination campaigns calls for
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Background-foreground segmentation for interior sensing in automotive industry J. Math. Industry Pub Date : 2022-12-30 Drygala, Claudia, Rottmann, Matthias, Gottschalk, Hanno, Friedrichs, Klaus, Kurbiel, Thomas
To ensure safety in automated driving, the correct perception of the situation inside the car is as important as its environment. Thus, seat occupancy detection and classification of detected instances play an important role in interior sensing. By the knowledge of the seat occupancy status, it is possible to, e.g., automate the airbag deployment control. Furthermore, the presence of a driver, which
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Reduced order multirate schemes in industrial circuit simulation J. Math. Industry Pub Date : 2022-08-20 Bannenberg, Marcus W. F. M., Ciccazzo, Angelo, Günther, Michael
In this paper the industrial application of Reduced Order Multirate (ROMR) schemes is presented. This paper contains the mathematical foundations of the ROMR schemes and elaborates on the construction of these schemes using specific Model Order Reduction (MOR) techniques. Especially the Maximum Entropy Snapshot Sampling method for generating a reduced basis and reduction by Gauß–Newton with Approximated
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Multirate DAE-simulation and its application in system simulation software for the development of electric vehicles J. Math. Industry Pub Date : 2022-08-17 Kolmbauer, Michael, Offner, Günter, Pfau, Ralf Uwe, Pöchtrager, Bernhard
This work is devoted to the efficient simulation of large multi-physical networks stemming from automated modelling processes in system simulation software. The simulation of hybrid, battery and fuel cell electric vehicle applications requires the coupling of electrical, mechanical, fluid, and thermal networks. Each network is established by combining the connection structure of a graph with physical
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A mathematical model for the corneal transparency problem J. Math. Industry Pub Date : 2022-05-06 Araújo, Adérito, Barbeiro, Sílvia, Bernardes, Rui, Morgado, Miguel, Sakić, Sunčica
Understanding the physical basis of corneal transparency has been a subject of interest amongst physicists, basic scientists and ophthalmologists. Impairment of corneal clarity is a significant cause of visual morbidity worldwide. Thus, it is essential to understand the mechanisms behind corneal transparency and how the alterations due to corneal pathologies affect vision. We use Maxwell’s equations
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An unambiguous cloudiness index for nonwovens J. Math. Industry Pub Date : 2022-04-04 Godehardt, Michael, Moghiseh, Ali, Oetjen, Christine, Ohser, Joachim, Schladitz, Katja
Cloudiness or formation is a concept routinely used in industry to address deviations from homogeneity in nonwovens and papers. Measuring a cloudiness index based on image data is a common task in industrial quality assurance. The two most popular ways of quantifying cloudiness are based on power spectrum or correlation function on the one hand or the Laplacian pyramid on the other hand. Here, we recall
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Hybrid modeling: towards the next level of scientific computing in engineering J. Math. Industry Pub Date : 2022-03-03 Kurz, Stefan, De Gersem, Herbert, Galetzka, Armin, Klaedtke, Andreas, Liebsch, Melvin, Loukrezis, Dimitrios, Russenschuck, Stephan, Schmidt, Manuel
The integration of machine learning (Keplerian paradigm) and more general artificial intelligence technologies with physical modeling based on first principles (Newtonian paradigm) will impact scientific computing in engineering in fundamental ways. Such hybrid models combine first principle-based models with data-based models into a joint architecture. This paper will give some background, explain
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Electric circuit element boundary conditions in the finite element method for full-wave passive electromagnetic devices J. Math. Industry Pub Date : 2022-02-23 Ciuprina, Gabriela, Ioan, Daniel, Sabariego, Ruth V.
A natural coupling of a circuit with an electromagnetic device is possible if special boundary conditions, called Electric Circuit Element (ECE), are used for the electromagnetic field formulation. This contribution shows how these ECE boundary conditions can be implemented into the 3D-finite element method for solving coupled full-wave electromagnetic (EM) field-circuit problems in the frequency domain
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On torque computation in electric machine simulation by harmonic mortar methods J. Math. Industry Pub Date : 2022-01-31 Egger, Herbert, Harutyunyan, Mané, Löscher, Richard, Merkel, Melina, Schöps, Sebastian
The use of trigonometric polynomials as Lagrange multipliers in the harmonic mortar method enables an efficient and elegant treatment of relative motion in the stator-rotor coupling of electric machine simulation. Explicit formulas for the torque computation are derived by energetic considerations, and their realization by harmonic mortar finite element and isogeometric analysis discretizations is
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Multistep schemes for solving backward stochastic differential equations on GPU J. Math. Industry Pub Date : 2022-01-28 Kapllani, Lorenc, Teng, Long
The Backward Stochastic Differential Equation (BSDE) is an important tool for pricing and hedging. Highly accurate pricing for low computation time becomes interesting for minimizing monetary loss. Therefore, we explore the opportunity of parallelizing high-order multistep schemes in option pricing. In the multistep scheme the computations at each space grid point are independent and this fact motivates
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Drift-diffusion models for the simulation of a graphene field effect transistor J. Math. Industry Pub Date : 2022-01-24 Nastasi, Giovanni, Romano, Vittorio
A field effect transistor having the active area made of monolayer graphene is simulated by a drift-diffusion model coupled with the Poisson equation. The adopted geometry, already proposed in (Nastasi and Romano in IEEE Trans. Electron. Devices 68:4729–4734, 2021, https://doi.org/10.1109/TED.2021.3096492 ), gives a good current-ON/current-OFF ratio as it is evident in the simulations. In this paper
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Pattern recognition in data as a diagnosis tool J. Math. Industry Pub Date : 2022-01-13 Carpio, Ana, Simón, Alejandro, Torres, Alicia, Villa, Luis F.
Medical data often appear in the form of numerical matrices or sequences. We develop mathematical tools for automatic screening of such data in two medical contexts: diagnosis of systemic lupus erythematosus (SLE) patients and identification of cardiac abnormalities. The idea is first to implement adequate data normalizations and then identify suitable hyperparameters and distances to classify relevant
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A technique for non-intrusive greedy piecewise-rational model reduction of frequency response problems over wide frequency bands J. Math. Industry Pub Date : 2022-01-03 Pradovera, Davide, Nobile, Fabio
In the field of model order reduction for frequency response problems, the minimal rational interpolation (MRI) method has been shown to be quite effective. However, in some cases, numerical instabilities may arise when applying MRI to build a surrogate model over a large frequency range, spanning several orders of magnitude. We propose a strategy to overcome these instabilities, replacing an unstable
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How deep is your model? Network topology selection from a model validation perspective J. Math. Industry Pub Date : 2022-01-03 Nowaczyk, Nikolai, Kienitz, Jörg, Acar, Sarp Kaya, Liang, Qian
Deep learning is a powerful tool, which is becoming increasingly popular in financial modeling. However, model validation requirements such as SR 11-7 pose a significant obstacle to the deployment of neural networks in a bank’s production system. Their typically high number of (hyper-)parameters poses a particular challenge to model selection, benchmarking and documentation. We present a simple grid
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Topology optimization subject to additive manufacturing constraints J. Math. Industry Pub Date : 2021-11-07 Ebeling-Rump, Moritz, Hömberg, Dietmar, Lasarzik, Robert, Petzold, Thomas
In topology optimization the goal is to find the ideal material distribution in a domain subject to external forces. The structure is optimal if it has the highest possible stiffness. A volume constraint ensures filigree structures, which are regulated via a Ginzburg–Landau term. During 3D printing overhangs lead to instabilities. As a remedy an additive manufacturing constraint is added to the cost
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Mechanical assessment of defects in welded joints: morphological classification and data augmentation J. Math. Industry Pub Date : 2021-10-30 Launay, Hugo, Willot, François, Ryckelynck, David, Besson, Jacques
We develop a methodology for classifying defects based on their morphology and induced mechanical response. The proposed approach is fairly general and relies on morphological operators (Angulo and Meyer in 9th international symposium on mathematical morphology and its applications to signal and image processing, pp. 226-237, 2009) and spherical harmonic decomposition as a way to characterize the geometry
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Quasi-3-D spectral wavelet method for a thermal quench simulation J. Math. Industry Pub Date : 2021-10-11 Bundschuh, Jonas, D’Angelo, Laura A. M., De Gersem, Herbert
The finite element method is widely used in simulations of various fields. However, when considering domains whose extent differs strongly in different spatial directions a finite element simulation becomes computationally very expensive due to the large number of degrees of freedom. An example of such a domain are the cables inside of the magnets of particle accelerators. For translationally invariant
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Mathematical and numerical analyses of a stochastic impulse control model with imperfect interventions J. Math. Industry Pub Date : 2021-09-26 Yoshioka, Hidekazu, Yaegashi, Yuta
A stochastic impulse control problem with imperfect controllability of interventions is formulated with an emphasis on applications to ecological and environmental management problems. The imperfectness comes from uncertainties with respect to the magnitude of interventions. Our model is based on a dynamic programming formalism to impulsively control a 1-D diffusion process of a geometric Brownian
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Mathematical models of the spread and consequences of the SARS-CoV-2 pandemics J. Math. Industry Pub Date : 2021-09-20 Micheletti, Alessandra, Araújo, Adérito, Budko, Neil, Carpio, Ana, Ehrhardt, Matthias
The SARS coronavirus 2 (SARS-CoV-2) pandemic of coronavirus disease-19 (COVID-19) has changed the lives of everyone on the planet. As a new disease with a significant mortality rate and no known pharmaceutical intervention or curative treatment to date, COVID-19 has stimulated a huge worldwide academic research effort on every aspect of the spread of the virus and the effectiveness of containment measures
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A greedy algorithm for optimal heating in powder-bed-based additive manufacturing J. Math. Industry Pub Date : 2021-08-19 Forslund, Robert, Snis, Anders, Larsson, Stig
Powder-bed-based additive manufacturing involves melting of a powder bed using a moving laser or electron beam as a heat source. In this paper, we formulate an optimization scheme that aims to control this type of melting. The goal consists of tracking maximum temperatures on lines that run along the beam path. Time-dependent beam parameters (more specifically, beam power, spot size, and speed) act
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Model order reduction for gas and energy networks J. Math. Industry Pub Date : 2021-07-18 Christian Himpe, Sara Grundel, Peter Benner
To counter the volatile nature of renewable energy sources, gas networks take a vital role. But, to ensure fulfillment of contracts under these circumstances, a vast number of possible scenarios, incorporating uncertain supply and demand, has to be simulated ahead of time. This many-query gas network simulation task can be accelerated by model reduction, yet, large-scale, nonlinear, parametric, hyperbolic
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On the impact of heterogeneity-aware mesh partitioning and non-contributing computation removal on parallel reservoir simulations J. Math. Industry Pub Date : 2021-06-30 Andreas Thune, Xing Cai, Alf Birger Rustad
Parallel computations have become standard practice for simulating the complicated multi-phase flow in a petroleum reservoir. Increasingly sophisticated numerical techniques have been developed in this context. During the chase of algorithmic superiority, however, there is a risk of forgetting the ultimate goal, namely, to efficiently simulate real-world reservoirs on realistic parallel hardware platforms
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Cost effective reproduction number based strategies for reducing deaths from COVID-19 J. Math. Industry Pub Date : 2021-06-28 Christopher Thron, Vianney Mbazumutima, Luis V. Tamayo, Léonard Todjihounde
In epidemiology, the effective reproduction number $R_{e}$ is used to characterize the growth rate of an epidemic outbreak. If $R_{e} >1$ , the epidemic worsens, and if $R_{e}< 1$ , then it subsides and eventually dies out. In this paper, we investigate properties of $R_{e}$ for a modified SEIR model of COVID-19 in the city of Houston, TX USA, in which the population is divided into low-risk and high-risk
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Optimal control of buoyancy-driven liquid steel stirring modeled with single-phase Navier–Stokes equations J. Math. Industry Pub Date : 2021-06-12 Ulrich Wilbrandt, Najib Alia, Volker John
Gas stirring is an important process used in secondary metallurgy. It allows to homogenize the temperature and the chemical composition of the liquid steel and to remove inclusions which can be detrimental for the end-product quality. In this process, argon gas is injected from two nozzles at the bottom of the vessel and rises by buoyancy through the liquid steel thereby causing stirring, i.e., a mixing
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Optimizing similarity factor of in vitro drug release profile for development of early stage formulation of drug using linear regression model J. Math. Industry Pub Date : 2021-06-05 Tulsi Sagar Sheth, Falguni Acharya
The objective of this article is to optimize the similarity factor within immediate release (IR) and modified release (MR) of in vitro drug release profiles. The least square method is used to minimize the difference between empirical and regression curve fitting data of in vitro IR/MR drug release profiles. An estimation of percentage drug release at intermediate timepoints has been done to improve
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Model order reduction for the simulation of parametric interest rate models in financial risk analysis J. Math. Industry Pub Date : 2021-06-03 Andreas Binder, Onkar Jadhav, Volker Mehrmann
This paper presents a model order reduction approach for large scale high dimensional parametric models arising in the analysis of financial risk. To understand the risks associated with a financial product, one has to perform several thousand computationally demanding simulations of the model which require efficient algorithms. We establish a model reduction approach based on a variant of the proper
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Stochastic perturbation of the Lighthill–Whitham–Richards model via the method of stochastic characteristics J. Math. Industry Pub Date : 2021-05-07 Nora Müller, Wolfgang Bock
In this paper we apply the method of stochastic characteristics to a Lighthill–Whitham–Richards model. The stochastic perturbation can be seen as errors in measurement of the traffic density. For concrete examples we solve the equation perturbed by a standard Brownian motion and the geometric Brownian motion without drift.
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Negative selection—a new performance measure for automated order execution J. Math. Industry Pub Date : 2021-03-23 Miles Kumaresan, Nataša Krejić, Sanja Lončar
Automated Order Execution is the dominant way of trading at stock markets. Performance of numerous execution algorithms is measured through slippage from some benchmark. But measuring true slippage in algorithmic execution is a difficult task since the execution as well as benchmarks are function of market activity. In this paper, we propose a new performance measure for execution algorithms. The measure
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Dynamics of epidemic diseases without guaranteed immunity J. Math. Industry Pub Date : 2021-02-22 Kurt Langfeld
The pandemic of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) suggests a novel type of disease spread dynamics. We here study the case where infected agents recover and only develop immunity if they are continuously infected for some time τ. For large τ, the disease model is described by a statistical field theory. Hence, the phases of the underlying field theory characterise the disease
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Inverse ray mapping in phase space for two-dimensional reflective optical systems J. Math. Industry Pub Date : 2021-02-04 Carmela Filosa, Jan ten Thije Boonkkamp, Wilbert IJzerman
A new method to compute the target photometric variables of non-imaging optical systems is presented. The method is based on the phase space representation of each surface that forms the optical system. All surfaces can be modeled as detectors of the incident light and emitters of the reflected light. Moreover, we assume that the source can only emit light and the target can only receive light. Therefore
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Pharmaceutical portfolio optimization under cost uncertainty via chance constrained-type method J. Math. Industry Pub Date : 2021-02-02 Maboubeh Farid, Abraar Chaudhry, Magnus Ytterstad, Stig Johan Wiklund
Project selection for a portfolio is a pivotal decision in the pharmaceutical industry. In this paper, we study a portfolio optimization problem for pharmaceutical companies considering the uncertainty of the cost of each phase of drug development and the specific value of the annual budget. The presented optimization model is suitable to make investment decisions for multi-phase drug development projects
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Flattening the curves: on-off lock-down strategies for COVID-19 with an application to Brazil J. Math. Industry Pub Date : 2021-01-06 Luís Tarrataca, Claudia Mazza Dias, Diego Barreto Haddad, Edilson Fernandes De Arruda
The current COVID-19 pandemic is affecting different countries in different ways. The assortment of reporting techniques alongside other issues, such as underreporting and budgetary constraints, makes predicting the spread and lethality of the virus a challenging task. This work attempts to gain a better understanding of how COVID-19 will affect one of the least studied countries, namely Brazil. Currently
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An epidemic model integrating direct and fomite transmission as well as household structure applied to COVID-19 J. Math. Industry Pub Date : 2021-01-05 Karunia Putra Wijaya, Naleen Ganegoda, Yashika Jayathunga, Thomas Götz, Moritz Schäfer, Peter Heidrich
This paper stresses its base contribution on a new SIR-type model including direct and fomite transmission as well as the effect of distinct household structures. The model derivation is modulated by several mechanistic processes inherent from typical airborne diseases. The notion of minimum contact radius is included in the direct transmission, facilitating the arguments on physical distancing. As
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Quantifying the shift in social contact patterns in response to non-pharmaceutical interventions J. Math. Industry Pub Date : 2020-12-01 Zachary McCarthy, Yanyu Xiao, Francesca Scarabel, Biao Tang, Nicola Luigi Bragazzi, Kyeongah Nah, Jane M. Heffernan, Ali Asgary, V. Kumar Murty, Nicholas H. Ogden, Jianhong Wu
Social contact mixing plays a critical role in influencing the transmission routes of infectious diseases. Moreover, quantifying social contact mixing patterns and their variations in a rapidly evolving pandemic intervened by changing public health measures is key for retroactive evaluation and proactive assessment of the effectiveness of different age- and setting-specific interventions. Contact mixing
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Linear behavior in Covid19 epidemic as an effect of lockdown J. Math. Industry Pub Date : 2020-11-30 Dario Bambusi, Antonio Ponno
We propose a mechanism explaining the approximately linear growth of Covid19 world total cases as well as the slow linear decrease of the daily new cases (and daily deaths) observed (in average) in USA and Italy. In our explanation, we regard a given population (the whole world or a single nation) as composed by many sub-clusters which, after lockdown, evolve essentially independently. The interaction
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Research on aircraft route planning optimization problem with multi-constraints and dual-targets J. Math. Industry Pub Date : 2020-10-28 Qianyu Zhang, Xianfeng Ding, Jingyu Zhou, Yi Nie
As the core technology in the field of aircraft, the route planning has attracted much attention. However, due to the complexity of the structure and performance constraints of the aircraft, the route planning algorithm does not have well universality, so it cannot be used in a complex environment. In the paper, a multi-constraints and dual-targets aircraft route planning model was established for
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A blackbox yield estimation workflow with Gaussian process regression applied to the design of electromagnetic devices J. Math. Industry Pub Date : 2020-10-07 Mona Fuhrländer, Sebastian Schöps
In this paper an efficient and reliable method for stochastic yield estimation is presented. Since one main challenge of uncertainty quantification is the computational feasibility, we propose a hybrid approach where most of the Monte Carlo sample points are evaluated with a surrogate model, and only a few sample points are reevaluated with the original high fidelity model. Gaussian process regression
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Data-driven graph drawing techniques with applications for conveyor systems J. Math. Industry Pub Date : 2020-10-02 Simone Göttlich, Sven Spieckermann, Stephan Stauber, Andrea Storck
The visualization of conveyor systems in the sense of a connected graph is a challenging problem. Starting from communication data provided by the IT system, graph drawing techniques are applied to generate an appealing layout of the conveyor system. From a mathematical point of view, the key idea is to use the concept of stress majorization to minimize a stress function over the positions of the nodes
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Beyond just "flattening the curve": Optimal control of epidemics with purely non-pharmaceutical interventions. J. Math. Industry Pub Date : 2020-08-18 Markus Kantner,Thomas Koprucki
When effective medical treatment and vaccination are not available, non-pharmaceutical interventions such as social distancing, home quarantine and far-reaching shutdown of public life are the only available strategies to prevent the spread of epidemics. Based on an extended SEIR (susceptible-exposed-infectious-recovered) model and continuous-time optimal control theory, we compute the optimal non-pharmaceutical
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An age and space structured SIR model describing the Covid-19 pandemic. J. Math. Industry Pub Date : 2020-08-08 Rinaldo M Colombo,Mauro Garavello,Francesca Marcellini,Elena Rossi
We present an epidemic model capable of describing key features of the Covid-19 pandemic. While capturing several qualitative properties of the virus spreading, it allows to compute the basic reproduction number, the number of deaths due to the virus and various other statistics. Numerical integrations are used to illustrate the adherence of the evolutions described by the model to specific well known
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Study on track planning problem of multi-constrained and double-targeted J. Math. Industry Pub Date : 2020-07-22 Yi Nie, Xiangjun Xie, Xianfeng Ding, Qianyu Zhang, Jingyu Zhou
Aiming at the positioning error of the aircraft, the error accumulation to a certain extent may lead to the failure of the mission. A track correction method based on oriented graph search was proposed, and the dynamic programming idea was applied to solve the path optimization problem. Firstly, the correction points in the flight space were preprocessed, and the planning of the correction points in
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Early stage COVID-19 disease dynamics in Germany: models and parameter identification. J. Math. Industry Pub Date : 2020-07-10 Thomas Götz,Peter Heidrich
Since the end of 2019 an outbreak of a new strain of coronavirus, called SARS-CoV-2, is reported from China and later other parts of the world. Since January 21, World Health Organization (WHO) reports daily data on confirmed cases and deaths from both China and other countries ( www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports ). The Johns Hopkins University ( github.com/
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Network-inspired versus Kozeny–Carman based permeability-porosity relations applied to Biot’s poroelasticity model J. Math. Industry Pub Date : 2020-07-06 Menel Rahrah, Luis A. Lopez-Peña, Fred Vermolen, Bernard Meulenbroek
Water injection in the aquifer induces deformations in the soil. These mechanical deformations give rise to a change in porosity and permeability, which results in non-linearity of the mathematical problem. Assuming that the deformations are very small, the model provided by Biot’s theory of linear poroelasticity is used to determine the local displacement of the skeleton of a porous medium, as well
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Modelling and simulation of flame cutting for steel plates with solid phases and melting J. Math. Industry Pub Date : 2020-06-24 Manuel J. Arenas, Dietmar Hömberg, Robert Lasarzik, Pertti Mikkonen, Thomas Petzold
The goal of this work is to describe in detail a quasi-stationary state model which can be used to deeply understand the distribution of the heat in a steel plate and the changes in the solid phases of the steel and into liquid phase during the flame cutting process. We use a 3D-model similar to previous works from Thiébaud (J. Mater. Process. Technol. 214(2):304–310, 2014) and expand it to consider
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Identification of the blood perfusion rate for laser-induced thermotherapy in the liver J. Math. Industry Pub Date : 2020-06-16 Matthias Andres, Sebastian Blauth, Christian Leithäuser, Norbert Siedow
Using PDE-constrained optimization we introduce a parameter identification approach which can identify the blood perfusion rate from MR thermometry data obtained during the treatment with laser-induced thermotherapy (LITT). The blood perfusion rate, i.e., the cooling effect induced by blood vessels, can be identified during the first stage of the treatment. This information can then be used by a simulation
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Mathematical modeling of vaporization during laser-induced thermotherapy in liver tissue J. Math. Industry Pub Date : 2020-06-03 Sebastian Blauth, Frank Hübner, Christian Leithäuser, Norbert Siedow, Thomas J. Vogl
Laser-induced thermotherapy (LITT) is a minimally invasive method causing tumor destruction due to heat ablation and coagulative effects. Computer simulations can play an important role to assist physicians with the planning and monitoring of the treatment. Our recent study with ex-vivo porcine livers has shown that the vaporization of the water in the tissue must be taken into account when modeling
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Quantifying the role of social distancing, personal protection and case detection in mitigating COVID-19 outbreak in Ontario, Canada. J. Math. Industry Pub Date : 2020-05-26 Jianhong Wu,Biao Tang,Nicola Luigi Bragazzi,Kyeongah Nah,Zachary McCarthy
Public health interventions have been implemented to mitigate the spread of coronavirus disease 2019 (COVID-19) in Ontario, Canada; however, the quantification of their effectiveness remains to be done and is important to determine if some of the social distancing measures can be relaxed without resulting in a second wave. We aim to equip local public health decision- and policy-makers with mathematical
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On the formation of centreline shrinkage porosity in the continuous casting of steel J. Math. Industry Pub Date : 2020-05-24 Michael Vynnycky
A recent asymptotic model for solidification shrinkage-induced macrosegregation in the continuous casting of binary alloys is extended for the purposes of understanding the link between solute segregation and centreline shrinkage porosity, a defect that commonly occurs in the continuous casting of steel. In particular, the analysis elucidates the relationship between microsegregation, mushy-zone permeability
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A new nonmonotone adaptive trust region line search method for unconstrained optimization J. Math. Industry Pub Date : 2020-04-10 Xinyi Wang, Xianfeng Ding, Quan Qu
This paper proposes a new nonmonotone adaptive trust region line search method for solving unconstrained optimization problems, and presents a modified trust region ratio, which obtained more reasonable consistency between the accurate model and the approximate model. The approximation of Hessian matrix is updated by the modified BFGS formula. Trust region radius adopts a new adaptive strategy to overcome