Article
Energy & Fuels
Jordan Jalving, Jaffer Ghouse, Nicole Cortes, Xian Gao, Bernard Knueven, Damian Agi, Shawn Martin, Xinhe Chen, Darice Guittet, Radhakrishna Tumbalam-Gooty, Ludovico Bianchi, Keith Beattie, Daniel Gunter, John D. Siirola, David C. Miller, Alexander W. Dowling
Summary: Future electricity generation systems need to be optimized to provide flexibility against the variability of renewable energy sources and ensure the reliability of critical infrastructure like the electric grid. Current state-of-the-art is to optimize the design and operation of integrated energy systems (IES) using fixed parameters for electricity prices. However, recent research has shown the limitations of this approach, and this paper proposes a new optimization formulation that incorporates IES market interactions using machine learning surrogate models, resulting in more accurate predictions.
Article
Materials Science, Multidisciplinary
Edgar O. Resendiz-Flores, Gerardo Altamirano-Guerrero, Patricia S. Costa, Antonio E. Salas-Reyes, Armando Salinas-Rodriguez, Frank Goodwin
Summary: This study applies a non-linear back-propagation artificial neural network to optimize the processing of hot-dip galvanized dual-phase steels, obtaining the best parameters through an evolutionary approach and achieving outstanding mechanical properties of GDP steels. This method is used for the first time in the design of an actual manufacturing process.
Article
Engineering, Mechanical
Cheng Wang
Summary: Gear modification is an effective technology to address vibration, noise, and uneven load distribution in gear transmission. By analyzing gear meshing contact, accurate performance data can be obtained, leading to optimization solutions for gear systems.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Thermodynamics
Adriana Zurita, Carlos Mata-Torres, Jose M. Cardemil, Rafael Guedez, Rodrigo A. Escobar
Summary: This study evaluates the impact of dispatch strategy on the optimal design configurations of various combinations of solar power plants with storage, using a multi-objective optimization approach to determine the least cost technological option.
Article
Computer Science, Artificial Intelligence
Raphael Pestourie, Youssef Mroueh, Chris Rackauckas, Payel Das, Steven G. Johnson
Summary: This study introduces a 'physics-enhanced deep-surrogate' (PEDS) approach for developing fast surrogate models for complex physical systems described by partial differential equations (PDEs). The PEDS approach combines a low-fidelity physics simulator and a neural network generator, trained end-to-end to match the output of a high-fidelity numerical solver. Experiments demonstrate that the PEDS surrogate is more accurate than a limited-data ensemble of feedforward neural networks and reduces the training data requirement.
NATURE MACHINE INTELLIGENCE
(2023)
Article
Thermodynamics
Jing Wang, Lixia Kang, Yongzhong Liu
Summary: This study proposes a two-step method to determine time series aggregation (TSA) strategies for multi-energy systems (MES) to optimize design and operation. Using a multi-objective optimization framework, the optimal TSA strategy is selected based on a combination of total system cost and loss of load probability as evaluation criteria.
Article
Computer Science, Artificial Intelligence
Dimitra G. Triantali, Konstantinos E. Parsopoulos, Isaac E. Lagaris
Summary: Artificial neural networks have become increasingly important in science and engineering, as they have proven to be useful in demanding applications. The challenge lies in training neural networks for large-scale problems using the stochastic gradient descent method, which requires diminishing step sizes. Variance counterbalancing was proposed as a remedy for this issue by minimizing the error variance along with the mean squared error. This approach promotes the use of advanced optimization algorithms instead of gradient descent.
APPLIED SOFT COMPUTING
(2023)
Article
Thermodynamics
Xiaoxiao Ren, Zijun Han, Jinpeng Ma, Kai Xue, Daotong Chong, Jinshi Wang, Junjie Yan
Summary: This study proposes a distributed multi-energy system driven by renewable energy sources and presents optimization models and operation strategies for reducing energy consumption and carbon emissions in data centers.
Article
Construction & Building Technology
Yukai Zou, Siwei Lou, Dawei Xia, Isaac Y. F. Lun, Jun Yin
Summary: Building performance is significantly influenced by weather conditions, and optimizing building performance under future climate conditions can greatly improve performance. This study demonstrates that considering future climate changes in optimization processes can lead to notable improvements in energy efficiency, thermal comfort, and daylighting performance, especially in hot and humid regions.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Multidisciplinary Sciences
Tong Wu, Jing Li, Xuan Qin
Summary: In order to enhance braking performance, engineers improve braking systems by upgrading structures and optimizing parameters, with multi-objective optimal design of electro-mechanical brake (EMB) parameters being an effective method. Research results show that this optimal design can reduce braking pressure response time, shorten stopping distance, increase mean fully developed deceleration, and reduce lateral displacement of the body.
Article
Computer Science, Information Systems
V. Pandiyaraju, Sannasi Ganapathy, N. Mohith, A. Kannan
Summary: Wireless Sensor Networks (WSNs) are crucial in Precision Agriculture for real-time data collection. Efficient energy utilization and Cluster Head (CH) selection processes are addressed using a multi-objective clustering approach and a hybrid optimization technique. The proposed method also improves clustering algorithm precision and training accuracy by combining optimization techniques with convolutional neural networks.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Li Yan, Zhipeng Zhang, Jing Liang, Boyang Qu, Kunjie Yu, Kongyuan Wang
Summary: This paper proposes an adaptive segmented multi-objective evolutionary network architecture search (ASMEvoNAS) method, which efficiently searches for network architectures through adaptive segmented evaluation strategy, preference-based pre-selection strategy, and novel gene reservation-based crossover and directed connection-based mutation. Experimental results demonstrate that ASMEvoNAS achieves promising performance on CIFAR-10, CIFAR-100, and ImageNet datasets.
APPLIED SOFT COMPUTING
(2023)
Article
Engineering, Multidisciplinary
Tao Xue, Long Chen, Jiexiang Hu, Qi Zhou
Summary: In this paper, a variable-fidelity hypervolume expected improvement (VF-HVEI) method is proposed to enhance the performance of existing multi-objective optimization algorithms. The method utilizes a Co-Kriging model to replace computationally expensive objective functions and sequentially updates it with the VF-HEVI method during the optimization process. Experimental results demonstrate that the proposed method achieves more accurate and robust Pareto front under the same simulation cost.
ENGINEERING OPTIMIZATION
(2023)
Article
Computer Science, Artificial Intelligence
Samuel Lopez-Ruiz, Carlos Hernandez-Castellanos, Katya Rodriguez-Vazquez
Summary: This paper proposes a novel approach, the stochastic directed search, for optimizing deep neural networks. The method allows efficient fine-tuning of neural networks and performs well in solving high-dimensional multi-objective problems. The effectiveness of the algorithm is demonstrated through experiments.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Construction & Building Technology
Amin Tanhadoust, Seyed Amir Ali Emadi, Sepideh Nasrollahpour, Farshad Dabbaghi, Moncef L. Nehdi
Summary: This research investigates the use of recycled crumb rubber as a partial replacement for fine aggregates in concrete. Through fracture analysis and Life Cycle Assessment, the study evaluates the damage and environmental impact of 10 different Recycled Rubber-Filled Concrete mixtures. Multi-objective optimization is used to identify the optimal mixture proportions, considering concrete characteristic objectives, environmental assessment, and cost constraints. The results show that increasing the crumb rubber content improves toughness and energy absorption but reduces compressive and tensile strengths. The study emphasizes the importance of carefully balancing water-to-cement ratio and crumb rubber content for achieving a balance of environmental impact, affordability, and performance.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Mechanics
Aashwin Ananda Mishra, Jayant Mukhopadhaya, Juan Alonso, Gianluca Iaccarino
Article
Mechanics
C. Garbacz, W. T. Maier, J. B. Scoggins, T. D. Economon, T. Magin, J. J. Alonso, M. Fossati
Summary: The study provides insights into shockwave interference patterns in gas flows with different gas mixtures. It reveals that freestream temperature significantly influences the non-equilibrium shock interaction patterns.
Article
Engineering, Aerospace
Catarina Garbacz, Fabio Morgado, Marco Fossati, Walter T. Maier, Brian C. Munguia, Juan J. Alonso, Adrien Loseille
Summary: In this study, flow patterns in shock/shock and shock/boundary-layer interactions around high-speed vehicles in hypersonic conditions were analyzed. Increasing the freestream Mach number resulted in changes in shock layer, shock impingement locations, and boundary-layer separation regions, with little impact on the overall shock interaction structures.
Article
Engineering, Aerospace
Marshall C. Galbraith, Carmen-Ioana Ursachi, Durgesh Chandel, Steven R. Allmaras, David L. Darmofal, Ryan S. Glasby, Douglas L. Stefanski, J. Taylor Erwin, Kevin R. Holst, Ethan A. Hereth, Jayant Mukhopadhaya, Juan J. Alonso
Summary: This study compares Reynolds-averaged Navier-Stokes (RANS) solutions for a multi-element airfoil computed with adaptive meshes generated by different solvers with manually generated meshes. The results show that adaptive meshes significantly reduce errors and node counts compared to manually generated meshes.
Article
Mechanics
Matthew A. Subrahmanyam, Brian J. Cantwell, Juan J. Alonso
Summary: This paper introduces a mixing length model for turbulent shear stress in pipe flow and provides a universal velocity profile. The velocity profile accurately approximates both experimental and simulated data in various flow conditions, making it significant for studying the statistical properties of flow.
JOURNAL OF FLUID MECHANICS
(2022)
Article
Engineering, Aerospace
Matthew A. Clarke, Juan J. Alonso
Summary: This paper introduces a method of integrating battery lifetime modeling into the assessment of all-electric aircraft and simulates different urban air mobility concepts. The study reveals that the battery life of achievable missions can decrease by as much as 45% depending on the vehicle configuration, range, and battery pack size. Additionally, there is a significant variation in the rate of change in operational lifetime.
JOURNAL OF AIRCRAFT
(2023)
Proceedings Paper
Engineering, Aerospace
Wesson Altoyan, Juan J. Alonso
Summary: The computational fluid dynamics (CFD) field has traditionally used the Navier-Stokes (NS) equations for fluid flow simulation, but this approach comes with high computational costs. The Lattice-Boltzmann method (LBM) offers a lower-cost alternative, achieving similar accuracy to NS equations by describing fluid behavior at a mesoscopic level. An ASIC LBM accelerator based on 16-nm technology shows potential for 33x performance improvement compared to GPUs and FPGAs.
2023 IEEE AEROSPACE CONFERENCE
(2023)
Proceedings Paper
Engineering, Aerospace
Dan Berkenstock, Juan Alonso, Laurent Lessard
Summary: This paper proposes an approach to the conceptual design of high-speed aerospace vehicles by addressing the interaction between hypersonic aerodynamics and radar cross section. The approach combines convex optimization with cubic splines as cross-sectional representations and demonstrates the creation of convex surrogates using piecewise linear functions and the application of convex constraints on geometry. A comparison is made between the ability of this convex optimization problem and a nonconvex sequential quadratic programming solver to converge to global optima.
2023 IEEE AEROSPACE CONFERENCE
(2023)
Article
Engineering, Aerospace
Matthew Clarke, Juan J. Alonso
Summary: This paper develops a semiempirical model for predicting degradation in lithium-ion batteries and evaluates the performance of a battery in a general aviation aircraft. Results indicate that the battery life can decrease by as much as 25% within a year of operation. The sensitivity of discharge rate and cycle depth of discharge to flight trajectory and environmental conditions is examined.
JOURNAL OF AIRCRAFT
(2021)
Article
Engineering, Aerospace
Walter T. Maier, Jacob T. Needels, Catarina Garbacz, Fabio Morgado, Juan J. Alonso, Marco Fossati
Summary: SU2-NEMO is a recent extension of the SU2 multiphysics suite, focusing on high-enthalpy and high-Mach number flows, utilizing thermal nonequilibrium and finite-rate chemistry models, and featuring a modular software architecture. The paper reviews the numerical formulation and discretization schemes for convective fluxes, and validates the performance of the solver through multiple test cases.
Proceedings Paper
Mathematics, Applied
Eduardo S. Molina, Daniel M. Silva, Andy P. Broeren, Marcello Righi, Juan J. Alonso
PROGRESS IN HYBRID RANS-LES MODELLING
(2020)
Proceedings Paper
Computer Science, Hardware & Architecture
Wesson Altoyan, Juan J. Alonso
28TH IEEE INTERNATIONAL SYMPOSIUM ON FIELD-PROGRAMMABLE CUSTOM COMPUTING MACHINES (FCCM)
(2020)
Article
Engineering, Multidisciplinary
Jayant Mukhopadhaya, Brian T. Whitehead, John F. Quindlen, Juan J. Alonso, Andrew W. Cary
INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION
(2020)
Proceedings Paper
Engineering, Aerospace
J. Michael Vegh, Emilio Botero, Matthew Clark, Jordan Smart, Juan J. Alonso
2019 AIAA/IEEE ELECTRIC AIRCRAFT TECHNOLOGIES SYMPOSIUM (EATS)
(2019)
Article
Green & Sustainable Science & Technology
Andres Santiago Padron, Jared Thomas, Andrew P. J. Stanley, Juan J. Alonso, Andrew Ning
WIND ENERGY SCIENCE
(2019)
Article
Computer Science, Interdisciplinary Applications
Vitaly Chernik, Pavel Buklemishev
Summary: The paper introduces a simple 2D model for describing the cell motility on a homogeneous isotropic surface. The model incorporates the dynamics of complex actomyosin liquid, which affects the boundary dynamics and cell motility. It consists of a system of equations with a free boundary domain and includes a non-local term. The numerical solution of this model is presented in this work.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Hasan Karjoun, Abdelaziz Beljadid
Summary: In this study, we developed a numerical model based on the depth-averaged shallow water equations to simulate flows through vegetation field. The model takes into account the drag and inertia forces induced by vegetation, using different formulations for the stem drag coefficient. Turbulence induced by vegetation is also considered through the addition of diffusion terms in the momentum equations. The proposed numerical model is validated through numerical simulations and shows good accuracy in simulating overland flows under vegetation effects.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Bechir Naffeti, Hamadi Ammar, Walid Ben Aribi
Summary: This paper proposes a branch and bound multidimensional Holder optimization method, which converts a multivariate objective function into a single variable function and minimizes it using an iterative optimization method. The method is applied to solve a parameters identification problem resulting from the increase in infections, providing information about the prevalence and infection force.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Heba F. Eid, Erik Cuevas, Romany F. Mansour
Summary: The proposed modified Bonobo optimizer algorithm dynamically adjusts the trajectory of each search agent to overcome the flaw of the original algorithm and improve the performance and solution quality by exploring and exploiting different regions of the solution space.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Farshid Mehrdoust, Idin Noorani, Juho Kanniainen
Summary: This paper proposes a Markov-switching model to evaluate the dynamics of commodity futures and spot prices, and introduces a hidden Markov chain to model the sudden jumps in commodity prices. The model is calibrated using the crude oil spot price and estimation-maximization algorithm. The study also evaluates European call options written on crude oil futures under the regime-switching model and derives Greek formulas for risk assessment. The importance of this paper is rated at 8 out of 10.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Rupa Mishra, Tapas Kumar Saha
Summary: This paper presents a control scheme for distributed generation units to operate in stand-alone and grid-connected modes, with a smooth transition between the two. The control strategy includes predictive control for voltage and frequency regulation in stand-alone mode, and power control for symmetrical and unbalanced grid voltage conditions in grid-connected mode. The proposed control method improves power factor, reduces grid current harmonics, and eliminates grid frequency ripple.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Yu Wang, Yang Tian, Yida Guo, Haoping Wang
Summary: This paper proposes a multi-level control strategy for lower limb patient-exoskeleton coupling system (LLPECS) in rehabilitation training based on active torque. The controller consists of three sub-controllers: gait adjustment layer, interaction torque design layer, and trajectory tracking layer. The effectiveness of the proposed control strategy is demonstrated through co-simulations in the SimMechanics environment using an exoskeleton virtual prototype developed in SolidWorks.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Takuji Arai, Yuto Imai
Summary: The Barndorff-Nielsen and Shephard model is a jump-type stochastic volatility model, and this paper proposes two simulation methods for computing option prices under a representative martingale measure. The performance of these methods is evaluated through numerical experiments.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Wanai Li
Summary: This paper proposes a new framework that combines quadrature-based and quadrature-free discontinuous Galerkin methods and applies them to triangular and tetrahedral grids. Four different DG schemes are derived by choosing specific test functions and collocation points, improving computational efficiency and ease of code implementation.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Xiyuan Chen, Qiubao Wang
Summary: This paper introduces a technique that combines dynamical mechanisms and machine learning to reduce dimensionality in high-dimensional complex systems. The method utilizes Hopf bifurcation theory to establish a model paradigm and utilizes machine learning to train location parameters. The effectiveness and robustness of the proposed method are tested and validated through experiments and simulations.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Muhammad Farman, Aqeel Ahmad, Anum Zehra, Kottakkaran Sooppy Nisar, Evren Hincal, Ali Akgul
Summary: Diabetes is a significant public health issue that affects millions of people worldwide. This study proposes a mathematical model to understand the mechanisms of glucose homeostasis, providing valuable insights for diabetes management. The model incorporates fractional operators and analyzes the impact of a new wave of dynamical transmission on equilibrium points, offering a comprehensive understanding of glucose homeostasis.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Gholamreza Shobeyri
Summary: This study introduces two improved Laplacian models for more accurate simulation of free surface flows in the context of the MPS method. The higher accuracy of these models compared to the traditional methods is verified through solving 2D Poisson equations and solving three benchmark free surface flow problems. These models can also resolve the issue of wave damping in the original MPS computations.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Qiang Li, Jinling Liang, Weiqiang Gong, Kai Wang, Jinling Wang
Summary: This paper addresses the problem of nonfragile state estimation for semi-Markovian switching complex-valued networks with time-varying delay. By constructing an event-triggered generator and solving matrix inequalities, less conservative criteria are obtained, and the gains of the nonfragile estimator are explicitly designed. A numerical example is provided to demonstrate the effectiveness of the proposed estimation scheme.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Gengen Zhang, Jingyu Li, Qiong-Ao Huang
Summary: In this paper, a novel class of unconditionally energy stable schemes are constructed for solving gradient flow models by combining the relaxed scalar auxiliary variable (SAV) approach with the linear multistep technique. The proposed schemes achieve second-order temporal accuracy and strictly unconditional energy stability.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
Article
Computer Science, Interdisciplinary Applications
S. Clain, J. Figueiredo
Summary: This study proposes a detailed construction of a very high-order polynomial representation and introduces a functional to assess the quality of the reconstruction. Several optimization techniques are implemented and their advantages in terms of accuracy and stability are demonstrated.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2024)
