Article
Energy & Fuels
Michael T. Castro, Joey D. Ocon
Summary: This study proposes a new methodology for generating reduced-order models and applies them in the techno-economic optimization of microgrids. Through simulations and optimizations of different chemistries, it is found that the idealized battery model can have significant discrepancies in certain scenarios.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Nanoscience & Nanotechnology
Gerard Rubi-Sans, Agata Nyga, Elena Rebollo, Soledad Perez-Amodio, Jorge Otero, Daniel Navajas, Miguel A. Mateos-Timoneda, Elisabeth Engel
Summary: The study introduced a novel method to produce mesenchymal cell-derived matrices (CDMs) aimed at mimicking the fibrotic tumor microenvironment, showing that they closely mimic the composition, structure, and mechanical properties of human fibrotic ECM. CDMs have highly reproducible composition and tunable mechanical properties, and exhibit increased doxorubicin resistance in cancer cells following chemotherapeutic treatment in comparison to 3D culture in collagen hydrogels.
ACS APPLIED MATERIALS & INTERFACES
(2021)
Article
Engineering, Geological
Anil Kumar, Roger Hu, Stuart D. C. Walsh
Summary: Fully coupled hydro-mechanical simulations of fractured media require sophisticated non-linear solvers to capture the complex relationship between fluid flow and material's mechanical response. Modelling these systems can be onerous, so a reduction strategy is necessary to predict physical response with less computational effort and time.
ROCK MECHANICS AND ROCK ENGINEERING
(2022)
Article
Physics, Fluids & Plasmas
Michael F. Herbst, Benjamin Stamm, Stefan Wessel, Matteo Rizzi
Summary: This article presents a methodology for investigating phase diagrams of quantum models using the reduced basis method. The method significantly reduces computational complexity and demonstrates accuracy in two test cases.
Article
Engineering, Multidisciplinary
Wawrzyniec J. Kostorz, Ann H. Muggeridge, Matthew D. Jackson
Summary: This paper introduces an intuitive geometrical framework for non-intrusive model reduction, allowing for a priori prediction and post-hoc explanation of model features. The proposed framework also includes a higher-order temporal discretization extension, demonstrating the representation of generic properties of physical systems. The study illustrates that the nonsmooth nature of the underlying non-intrusive reduced order modeling may lead to a poor system dynamics representation.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2021)
Article
Engineering, Mechanical
Jaeyong Kim, Gang-Won Jang, Yoon Young Kim
Summary: In this study, a new method is proposed to address the issue of connection conditions for higher-order beam elements. The proposed method utilizes the vertices and intersection points of a joint section and imposes continuity conditions using Lagrange multipliers. Unlike previous studies, this method is applicable to beam frame structures with general section shapes without relying on geometric conditions.
INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
(2022)
Article
Business, Finance
Luc Bauwens, Edoardo Otranto
Summary: This article discusses modeling of time series of realized covariance matrices using dynamic correlations or dynamic covariances in the conditional autoregressive Wishart model family. The proposed extended parameterizations ensure the positive definiteness of the conditional covariance or correlation matrix with simple parametric restrictions, while maintaining a fixed or linear number of parameters relative to the number of assets. Empirical studies demonstrate that the extended models outperform simpler versions and benchmark models in forecasting performance.
JOURNAL OF FINANCIAL ECONOMETRICS
(2023)
Article
Physics, Multidisciplinary
Ingolf Bischer, Christian Doering, Andreas Trautner
Summary: A set of non-defect matrices can be simultaneously diagonalized only if they commute; otherwise, simultaneous block diagonalization is the best that can be achieved. This paper presents an efficient algorithm to compute a transfer matrix for block diagonalizing unitary matrices with known decompositions into irreducible blocks, particularly motivated by applications in particle physics.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2021)
Article
Engineering, Multidisciplinary
P. Solan-Fustero, J. L. Gracia, A. Navas-Montilla, P. Garcia-Navarro
Summary: In this study, a Roe-based reduced-order model is developed to efficiently solve the shallow water equations with source terms, compared to the Roe-based full-order model. The augmented Riemann solvers are used to consider the well-balanced property, entropy fix, and wet-dry treatment in constructing the Roe-based full-order model. Additionally, a time averaging approach is necessary for developing the Roe-based reduced-order model. The approach is validated through solving test cases and comparing the computed solutions with those of Lax-Friedrichs-based reduced-order models.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
M. H. Nagaraj, J. Reiner, R. Vaziri, E. Carrera, M. Petrolo
Summary: This paper presents a refined progressive damage analysis method for fiber-reinforced laminated composites under compressive loads, utilizing higher-order structural theories and numerical assessments to verify its effectiveness.
COMPOSITES PART B-ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
Jie Yuan, Kundong Wang, Huaming Lei, Baiming Li
Summary: This paper proposes a novel mathematical model for inductive displacement sensors based on a multi-objective optimization algorithm, which has high accuracy. The model uses composite functions to establish the coil winding's structural parameters. The non-dominated sorting genetic algorithm II (NSGA-II) is employed to solve non-dominated problems related to the coil structure parameters, aiming for superior sensor performance. Density clustering sorting is utilized to select the desired non-dominated solutions. The designed sensor has a nonlinearity of 0.16%, and numerical simulations and physical experiments confirm the effectiveness of the new design method.
Article
Mathematics, Applied
R. B. Beshimov, D. Georgiou, F. Sereti
Summary: The dimensions of partially ordered sets, lattices, and frames have been a subject of interest for researchers. Matrix algebra plays an important role in studying these dimensions. In this paper, we investigate the small inductive dimension for finite lattices using matrices and propose an algorithmic procedure for computing it.
COMPUTATIONAL & APPLIED MATHEMATICS
(2023)
Article
Chemistry, Multidisciplinary
Ji Hee Kim, Geun Bae Rhim, Naeun Choi, Min Hye Youn, Dong Hyun Chun, Seongmin Heo
Summary: Fischer-Tropsch synthesis (FTS) is a sustainable method for producing various chemicals and fuels, and this study proposes a hybrid modeling framework to efficiently build a kinetic model for FTS. The framework is validated using experimental data, and it shows promising results in predicting the consumption and production rates as well as the optimal operating conditions for FTS.
JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY
(2023)
Article
Mathematics, Applied
Tibor Joedan, Shin-Ichi Tanigawa
Summary: This study examines the rigidity properties of random subgraphs using the random subgraph model. New upper bounds for the rigidity threshold are derived, with particular focus on the Erdos-Renyi random graph model. The study also considers random subframeworks and bond-bending networks, providing upper bounds for the rigidity threshold in these contexts. The concept of d-dimensional algebraic connectivity is introduced and bounds for this value are provided for various graph classes.
SIAM JOURNAL ON DISCRETE MATHEMATICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Cong Xiao, Olwijn Leeuwenburgh, Hai Xiang Lin, Arnold Heemink
Summary: A reduced order modeling algorithm is proposed for estimating space varying parameter patterns in numerical models. Domain decomposition is used to construct separate approximations in each subdomain, with a new local parameterization to decouple computational cost from global principal components. This approach drastically reduces the number of full order simulations needed for deriving reduced order models, with optimal local parameter patterns projected onto global patterns to avoid non-smoothness at subdomain boundaries.
JOURNAL OF COMPUTATIONAL PHYSICS
(2021)
Article
Computer Science, Information Systems
Philip Hake, Jana-Rebecca Rehse, Peter Fettke
Summary: This paper explores how available data can be used to automate support for complaint handling processes in medical technology companies. By designing a deep learning prototype, partial process automation was successfully achieved with promising results in practice.
JOURNAL ON DATA SEMANTICS
(2021)
Article
Computer Science, Information Systems
Marlon Dumas, Fabiana Fournier, Lior Limonad, Andrea Marrella, Marco Montali, Jana-Rebecca Rehse, Rafael Accorsi, Diego Calvanese, Giuseppe De Giacomo, Dirk Fahland, Avigdor Gal, Marcello La Rosa, Hagen Voelzer, Ingo Weber
Summary: AI-augmented Business Process Management Systems (ABPMSs) are a new class of process-aware information systems empowered by trustworthy AI technology. These systems aim to improve the execution of business processes by making them more adaptable, proactive, explainable, and context-sensitive. This manifesto presents a vision for ABPMSs and discusses the research challenges that need to be overcome to achieve this vision. It defines the concept of ABPMS, outlines the lifecycle of processes within an ABPMS, discusses core characteristics, and identifies challenges for realizing systems with these characteristics.
ACM TRANSACTIONS ON MANAGEMENT INFORMATION SYSTEMS
(2023)
Proceedings Paper
Business
Adrian Rebmann, Jana-Rebecca Rehse, Han van der Aa
Summary: This paper introduces a method for transforming classical event logs into object-centric event logs. The transformation can solve the issue of hidden relationships between objects in classical event logs. By combining semantic analysis, data profiling, and control-flow-based relation extraction techniques, object-related information in flat event data can be automatically uncovered and transformed into object-centric event logs.
BUSINESS PROCESS MANAGEMENT (BPM 2022)
(2022)
Proceedings Paper
Business
Luka Abb, Jana-Rebecca Rehse
Summary: User interaction (UI) logs are high-resolution event logs that record the low-level activities performed by users during the execution of a task in an information system. However, the lack of standardization makes it challenging to integrate UI logs from different sources and combine them with downstream analytics or automation solutions. This paper proposes a universally applicable reference data model for process-related UI logs and demonstrates its practical applicability in a real-life RPA scenario.
BUSINESS PROCESS MANAGEMENT (BPM 2022)
(2022)
Proceedings Paper
Business
Simone Agostinelli, Andrea Marrella, Luka Abb, Jana-Rebecca Rehse
Summary: This paper discusses how process mining can be used to minimize manual and time-consuming steps in RPA, enabling more automation in the creation of software robots. The paper presents a reference data model and a pipeline of processing steps, and demonstrates the implementation of this pipeline using the SmartRPA tool.
BUSINESS PROCESS MANAGEMENT (BPM 2022)
(2022)
Proceedings Paper
Business
Fareed Zandkarimi, Jonas Rennemeier, Jana-Rebecca Rehse
Summary: Efficiency is a key dimension for evaluating organizational performance, and process inefficiencies can lead to resource waste and failure to achieve internal goals. This paper introduces a new method for measuring process inefficiencies, showing that it captures aspects not considered by other methods.
BUSINESS PROCESS MANAGEMENT FORUM (BPM 2021)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Fareed Zandkarimi, Jana-Rebecca Rehse, Pouya Soudmand, Hartmut Hoehle
2020 2ND INTERNATIONAL CONFERENCE ON PROCESS MINING (ICPM 2020)
(2020)
Article
Computer Science, Artificial Intelligence
Jana-Rebecca Rehse, Nijat Mehdiyev, Peter Fettke
KUNSTLICHE INTELLIGENZ
(2019)
Article
Engineering, Industrial
Jana-Rebecca Rehse, Peter Fettke
ENTERPRISE MODELLING AND INFORMATION SYSTEMS ARCHITECTURES-AN INTERNATIONAL JOURNAL
(2019)
Proceedings Paper
Business
Jana-Rebecca Rehse, Peter Fettke, Peter Loos
BUSINESS PROCESS MANAGEMENT WORKSHOPS (BPM 2017)
(2018)
Proceedings Paper
Business
Johannes Tenschert, Jana-Rebecca Rehse, Peter Fettke, Richard Lenz
BUSINESS PROCESS MANAGEMENT WORKSHOPS (BPM 2017)
(2018)
Article
Computer Science, Artificial Intelligence
Joerg Evermann, Jana-Rebecca Rehse, Peter Fettke
DECISION SUPPORT SYSTEMS
(2017)
Proceedings Paper
Business
Joerg Evermann, Jana-Rebecca Rehse, Peter Fettke
BUSINESS PROCESS MANAGEMENT WORKSHOPS, BPM 2016
(2017)
Article
Computer Science, Information Systems
Jana-Rebecca Rehse, Sharam Dadashnia, Peter Fettke
IT-INFORMATION TECHNOLOGY
(2018)