Article
Computer Science, Interdisciplinary Applications
Qiong Wang, Zhiwei Liu, Liang Cao, Zhao Xiao, Qunwang Zhang, Shuo Zhang
Summary: This paper combines a multidimensional parallelepiped model with a multiobjective genetic algorithm (GA) for the design of the vehicle occupant restraint system (ORS). By considering interval uncertainties and correlations, a multiobjective optimization model is developed, and the optimization problem is solved using the interval expansion method. The application example shows that correlations have an impact on the optimization results, and neglecting correlation analysis may lead to design deviations.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Soil Science
Luciana Chavez Rodriguez, Ana Gonzalez-Nicolas, Brian Ingalls, Thilo Streck, Wolfgang Nowak, Sinan Xiao, Holger Pagel
Summary: This study applies prospective optimal design of experiments to identify laboratory sampling strategies that allow model-based discrimination of pesticide degradation pathways. The results highlight the importance of measuring pesticide metabolites for understanding pesticide fate in the environment. The study emphasizes the use of model-based prospective optimal design to maximize knowledge gains on soil systems from laboratory and field experiments.
EUROPEAN JOURNAL OF SOIL SCIENCE
(2022)
Article
Chemistry, Multidisciplinary
Abhishek Kumar, Xiangning He, Yan Deng, Arvind R. Singh, Bikash Sah, Praveen Kumar, R. C. Bansal, M. Bettayeb, Ramesh Rayudu
Summary: This study proposes a sustainable microgrid design framework that utilizes locally accessible energy sources for rural electrification. The framework combines social-political evaluation, techno-market analysis, feasibility analysis, and environmental-economic analysis to determine the optimal electrification solution.
ENERGY & ENVIRONMENTAL SCIENCE
(2022)
Article
Mechanics
F. Moleiro, J. F. A. Madeira, E. Carrera, A. J. M. Ferreira
Summary: This study focuses on the multiobjective design optimization of sandwich plates with ceramic-metal-ceramic functionally graded cores, considering symmetric and non-symmetric configurations under thermo-mechanical loadings. The thermal and mechanical problems are fully coupled using a mixed least-squares model with multi-field independent variables, and the optimization problem is solved by a derivative-free method. The numerical results provide optimal designs for validation, taking into account different constituent materials.
COMPOSITE STRUCTURES
(2021)
Article
Engineering, Chemical
Anh-Duong Dieu Vo, Ali Shahmohammadi, Kimberley B. McAuley
Summary: Sequential model-based design of experiments (MDBOE) is used to select operating conditions for a batch reactor producing bio-based polytrimethylene ether glycol (PO3G). Bayesian A-optimal experiments are designed to improve estimates of 70 fundamental-model parameters while considering industrial data from previous runs. The effectiveness of the proposed MBDOE approach is tested using Monte-Carlo simulations, showing that the selected experiments outperform randomly selected ones from the design space.
Article
Green & Sustainable Science & Technology
Seon Woo Kim, Soon Ho Kwon, Donghwi Jung
Summary: In this study, a multiobjective automatic parameter-calibration framework based on the stormwater management model (SWMM) was developed to improve the sustainability of urban drainage systems (UDSs). The proposed framework was verified using the Yongdap drainage network in Seoul, South Korea, and showed its effectiveness in reflecting system characteristics and problems in UDS design, planning, and management.
Article
Computer Science, Interdisciplinary Applications
Boeun Kim, Kyung Hwan Ryu, Seongmin Heo
Summary: This article introduces a new optimality criterion for model-based design of experiments, which can address the issues encountered by conventional criteria in practical systems. Results from a comparative experiment using a linear example demonstrate that the proposed criterion outperforms the conventional ones in all cases.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Article
Materials Science, Multidisciplinary
Vasileios Sergis, Claudiane M. Ouellet-Plamondon
Summary: The development of 3D printable cement-based materials is a complex process with competing objectives. This study introduces the use of D-optimal experimental design to reduce workload and obtain high-quality results. The research findings demonstrate the effectiveness of D-optimal mix design in reducing workload and assessing the importance of each factor and level.
MATERIALS & DESIGN
(2022)
Article
Green & Sustainable Science & Technology
Nayara R. M. Sakiyama, Joyce C. Carlo, Leonardo Mazzaferro, Harald Garrecht
Summary: Performance-based design using computational and parametric optimization is an effective strategy for solving multiobjective problems typical of building design. This study investigates the process of parametric modeling and optimization of a naturally ventilated house, aiming to maximize natural ventilation effectiveness and reduce annual building energy demand. Results show great potential for energy savings in natural ventilation and heating for residential buildings, with improvements ranging from 14-87% and 26-34% in NVE and THL, respectively.
Article
Automation & Control Systems
Dayuan Wu, Ping Yan, You Guo, Han Zhou, Runzhong Yi
Summary: The paper proposes a helical gear processing parameter optimization method, which establishes a multi-objective optimization model and designs an adaptive evolution algorithm to achieve comprehensive optimization of efficiency, cost, and precision.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Health Care Sciences & Services
Menglu Che, Feng Xie, Stephanie Thomas, Eleanor Pullenayegum
Summary: This study compared different models for predicting the value sets of EQ-5D-5L and found that Bayesian models with spatial correlation and CALE models can improve the precision of the value sets.
MEDICAL DECISION MAKING
(2023)
Article
Oncology
Alessandro Vasciaveo, Juan Martin Arriaga, Francisca Nunes de Almeida, Min Zou, Eugene F. Douglass Jr, Florencia Picech, Maho Shibata, Antonio Rodriguez-Calero, Simone de Brot, Antonina Mitrofanova, Chee Wai Chua, Charles Karan, Ronald Realubit, Sergey Pampou, Jaime Y. Kim, Stephanie N. Afari, Timur Mukhammadov, Luca Zanella, Eva Corey, Mariano J. Alvarez, Mark A. Rubin, Michael M. Shen, Andrea Califano, Cory Abate-Shen
Summary: OncoLoop is a precision medicine framework that predicts drug sensitivity in human tumors and their preexisting high-fidelity models by leveraging drug perturbation profiles. It has been successfully applied to prostate cancer study and validated the predicted drugs.
Article
Pharmacology & Pharmacy
Francesca Cenci, Gabriele Bano, Charalampos Christodoulou, Yuliya Vueva, Simeone Zomer, Massimiliano Barolo, Fabrizio Bezzo, Pierantonio Facco
Summary: This study examines the impact of powder lubricant selection on tablet manufacturing in direct compression solid dosage production, proposing a new method to reduce experimental workload and successfully achieve a 60-70% reduction in experimental effort.
INTERNATIONAL JOURNAL OF PHARMACEUTICS
(2022)
Article
Engineering, Multidisciplinary
Tristan Gally, Peter Groche, Florian Hoppe, Anja Kuttich, Alexander Matei, Marc E. Pfetsch, Martin Rakowitsch, Stefan Ulbrich
Summary: In engineering applications, models are used to describe processes, particularly in forming machines. This paper proposes a method to identify model uncertainty using parameter identification, optimal design of experiments, and hypothesis testing. By optimizing sensor positions, specific model parameters can be determined and confidence regions can be computed.
OPTIMIZATION AND ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Yuming Ning, Tuanjie Li, Wenqian Du, Cong Yao, Yan Zhang, Jisheng Shao
Summary: This paper proposes two novel algorithms, namely the Improved Adaptive Particle Swarm Optimization (APSO) algorithm and the Planning/Control Codesign (PCC) algorithm based on Dynamic Movement Primitives (DMPs-PCC), to improve the operating accuracy and operating efficiency of the 7-DoF redundant manipulator.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Engineering, Chemical
Qiao Li, Zemin Feng, G. P. Rangaiah, Lichun Dong
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2020)
Review
Engineering, Chemical
Gade Pandu Rangaiah, Zemin Feng, Andrew F. Hoadley
Article
Engineering, Chemical
Zhiyuan Wang, Gade Pandu Rangaiah, Xiaonan Wang
Summary: This paper introduces a novel MCDM method PROBID and its simplified variant sPROBID for multi-objective optimization in chemical engineering. Results show that PROBID is more consistent and robust in ranking compared to other MCDM methods tested, while sPROBID outperforms four out of seven methods in terms of ranking consistency.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Zemin Feng, Wenhe Wang, Di Xu, Gade Pandu Rangaiah, Lichun Dong
Summary: The investigation of dynamic controllability of double liquid-only side-stream distillation (DLSD) is necessary due to its good potential for separating multicomponent mixtures in industrial practice. This study proposed three temperature control schemes without composition measurement for DLSD, and the results demonstrate that CS3 provides better control for DLSD than CS1 and CS2.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Article
Engineering, Chemical
Anikesh Kumar, Lakshminarayanan Samavedham, Iftekhar A. Karimi, Rajagopalan Srinivasan
Summary: Safety and economic constraints in industrial processes are not well handled by conventional control systems, leading to the addition of ad hoc elements and more sophisticated control strategies. Recent developments suggest model predictive control (MPC) as a more natural approach. This work evaluates the efficacy of ad hoc additions to handle constraints and applies it to a continuously stirred tank reactor model and a heat exchanger system, demonstrating the limitations of the approach and the improvement achieved with MPC.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Zhiyuan Wang, Jie Li, Gade Pandu Rangaiah, Zhe Wu
Summary: A machine learning aided multi-objective optimization and multi-criteria decision making framework is proposed for chemical engineering applications. It has been shown to be effective in optimizing complex chemical processes.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Article
Energy & Fuels
Shivom Sharma, Iftekhar A. Karimi, Shamsuzzaman Farooq, Lakshminarayanan Samavedham, Rajagopalan Srinivasan
Summary: Mathematical models were developed for spring-loaded and lever-type regulators to diagnose faults, track prognoses, and estimate remaining useful life. The proposed methodologies were validated using real data and packaged into a user-friendly dashboard for industrial use.
Article
Engineering, Chemical
Seyed Reza Nabavi, Zhiyuan Wang, Gade Pandu Rangaiah
Summary: Optimization for multiple objectives has gained significant attention in academia. This paper investigates the sensitivity of multi-criteria decision making (MCDM) methods, focusing on the phenomena of rank reversal. The research evaluates the effect of three modifications on the ranking of Pareto-optimal solutions and provides useful findings for MCDM application and further research.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Rasel Ahmed, Gade Pandu Rangaiah, Shuhaimi Mahadzir, Seyedali Mirjalili, Mohamed H. Hassan, Salah Kamel
Summary: This work proposes an improved grey wolf optimization algorithm that addresses the limitations in terms of population diversity, premature convergence, and the balance between exploration and exploitation behavior. The proposed algorithm incorporates memory, evolutionary operators, stochastic local search, and a linear population size reduction technique. Experimental results show that the proposed algorithm outperforms other popular metaheuristics in various benchmark functions and engineering case studies.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Zhiyuan Wang, Wallace Gian Yion Tan, Gade Pandu Rangaiah, Zhe Wu
Summary: This paper proposes a machine learning-aided multi-objective optimization and multi-criteria decision-making method for chemical process control. The evaluation on a continuous stirred tank reactor demonstrates the capability of this method to achieve multi-objective optimization without compromising closed-loop stability. The study also confirms the feasibility of using machine learning models in process control and optimization.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Proceedings Paper
Automation & Control Systems
Shahla Alizadeh, Souvik Ta, Ajay K. Ray, S. Lakshminarayanan
Summary: This study investigates the use of Fourier Transform Infrared (FTIR) spectroscopy combined with chemometric methods for quantification of crude oil properties. Crude oil samples from seven different Canadian fields were analyzed, and different methods such as PLS, PCA, iPLS, and PLS-GA were compared for model building. The results show that the best quantification results for density and viscosity were obtained using partial least squares (PLS) regression on FTIR data.
Proceedings Paper
Automation & Control Systems
Aditi Sharma, Ravindra Gudi, Lakshminarayanan Samavedham
Summary: This paper describes a novel approach to establish comfortable conditions while optimizing energy consumption using a comfort control-based method. The results show that a two-level control architecture can effectively control setpoints and fan load.
2022 IEEE INTERNATIONAL SYMPOSIUM ON ADVANCED CONTROL OF INDUSTRIAL PROCESSES (ADCONIP 2022)
(2022)
Proceedings Paper
Automation & Control Systems
Yue Yifei, S. Lakshminarayanan
Summary: This study used a Multi-Agent Reinforcement Learning (MARL) control system to control a multiloop CSTR process, achieving stable closed-loop response and good disturbance rejection.
2022 IEEE INTERNATIONAL SYMPOSIUM ON ADVANCED CONTROL OF INDUSTRIAL PROCESSES (ADCONIP 2022)
(2022)
Proceedings Paper
Automation & Control Systems
Suparna Samavedham, S. Lakshminarayanan
Summary: This research applies recent findings on the vulnerability of cyber-physical systems to detect their robustness to stealthy attacks. The aim is to minimize the impact of attacks on bottom line safety and performance.
2021 60TH ANNUAL CONFERENCE OF THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS OF JAPAN (SICE)
(2021)
Proceedings Paper
Automation & Control Systems
Shivom Sharma, S. Lakshminarayanan, I. A. Karimi, R. Srinivasan
Summary: This study applies convergent cross-mapping technique and standard statistical techniques to monitor operation, detect faults, and identify root causes in non-linear dynamic systems. It focuses on detecting sensor and process faults, and visualizing fault propagation through causal link lists. The correctness of the generated causal link lists has been validated with existing process knowledge.
2021 60TH ANNUAL CONFERENCE OF THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS OF JAPAN (SICE)
(2021)