1,359,072 research outputs found
Automatic balancing parameter selection for Tikhonov-TV regularization
No full textThis paper considers large-scale linear ill-posed inverse problems whose solutions can be represented as sums of smooth and piecewise constant components. To solve such problems we consider regularizers consisting of two terms that must be balanced. Namely, a Tikhonov term guarantees the smoothness of the smooth solution component, while a total-variation (TV) regularizer promotes blockiness of the non-smooth solution component. A scalar parameter allows to balance between these two terms and, hence, to appropriately separate and regularize the smooth and non-smooth components of the solution. This paper proposes an efficient algorithm to solve this regularization problem by the alternating direction method of multipliers (ADMM). Furthermore, a novel algorithm for automatic choice of the balancing parameter is introduced, using robust statistics. The proposed approach is supported by some theoretical analysis, and numerical experiments concerned with different inverse problems are presented to validate the choice of the balancing parameter
Robust estimation of structural orientation parameters and 2D/3D local anisotropic Tikhonov regularization
No full textUnderstanding the orientation of geologic structures is crucial for analyzing the complexity of the earths' subsurface. For instance, information about geologic structure orientation can be incorporated into local anisotropic regularization methods as a valuable tool to stabilize the solution of inverse problems and produce geologically plausible solutions. We introduce a new variational method that uses the alternating direction method of multipliers within an alternating minimization scheme to jointly estimate orientation and model parameters in 2D and 3D inverse problems. Specifically, our approach adaptively integrates recovered information about structural orientation, enhancing the effectiveness of anisotropic Tikhonov regularization in recovering geophysical parameters. The paper also discusses the automatic tuning of algorithmic parameters to maximize the new method's performance. Our algorithmis tested across diverse 2D and 3D examples, including structure-oriented denoising and trace interpolation. The results indicate that the algorithm is robust in solving the considered large and challenging problems, alongside efficiently estimating the associated tilt field in 2D cases and the dip, strike, and tilt fields in 3D cases. Synthetic and field examples show that our anisotropic regularization method produces a model with enhanced resolution and provides a more accurate representation of the true structures
Identification of high potential zones for hydrocarbon production based on fracture aperture estimation using hybridised intelligent systems: Datasets and Supplementary Materials
No full text******************* Please find more detailed descriptions of data, computer codes and results in the Readme.txt file. ********************Title: Identification of high potential zones for hydrocarbon production based on fracture aperture estimation using hybridised intelligent systems: Datasets and Supplementary Materials.Version: 1.0Date of Release: 2022/10/18Identifier: doi: 10.17632/35th6nxwdh.1Permalink: http://dx.doi.org/10.17632/35th6nxwdh.1By: Ali Gholami Vijouyeh, Ali Kadkhodaie, Mohammad Hassanpour Sedghi, Hamed Gholami VijouyehContact information: Ali Gholami Vijouyeh, Earth Sciences Department, Faculty of Natural Science, University of Tabriz, Tabriz, Iran, [email protected] DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV
A Scalable Framework for Multi-Robot Tele-Impedance Control
No full textIn this article, we present an online scalable tele-impedance framework, which enables the individual and collaborative control of multiple different robotic platforms. The framework provides an intuitive low-cost interface with visual feedback and a SpaceMouse, through which the operator can define the desired task-level trajectories and impedance profiles. With a simple mouse click, the user can switch between the robots and the collaborative operation mode. The control, subsequently, manages the distribution of the required parameters into the involved robots. Thanks to the introduced virtual hand concept, where each robot is defined as a finger, new robots can be easily added or removed via their kinodynamic parameters. The proposed framework was evaluated with three different experiments: a simulated auscultation on a mock-up patient, a cooperative task where a robot drives the patient on a wheelchair and a different robot performs the auscultation, and a collaborative task where two robots relocate a container. The results demonstrate the capabilities of the framework in terms of adaptability to different robotic platforms, the number of robots involved, and the task requirements. Additionally, quantitative and subjective analysis of 12 subjects showed how the developed interface, even in the presence of inaccurate visual feedback, allowed a smooth and accurate execution of the tasks
Generation Capacity Expansion with CO2 Emission and Transmission Constraints in an Oligopolistic Market
No full textThe European Union is committed to cut Greenhouse Gas emissions (GHGs) by 30% of 1990 levels by 2020; other countries are committed to make similar reductions under a global agreement. Some technical options are available on the supply side, to reduce GHG and other harmful emissions by the power sector. Therefore, it is important to analyze what type of power generation technologies will be chosen by companies under different CO2 mitigation targets. Several models look into Generation Expansion Planning in oligopolistic markets; however, they do not consider the impact of CO2 reduction targets and the transmission constraints together. This study presents a Generation Expansion planning model with transmission constraints for analyzing the implications of CO2 emission mitigation constraints for investment decisions in oligopolistic electricity markets. The results of the model are presented with reference to the Italian power sector, responsible for 32% of national CO2 emissions
Identification of high potential zones for hydrocarbon production based on fracture aperture estimation using hybridised intelligent systems: Datasets and Supplementary Materials
No full textTitle: Identification of high potential zones for hydrocarbon production based on fracture aperture estimation using hybridised intelligent systems: Datasets and Supplementary Materials.Version: 1.0Date of Release: 2022/10/18Identifier: doi: 10.17632/35th6nxwdh.1Permalink: http://dx.doi.org/10.17632/35th6nxwdh.1By: Ali Gholami Vijouyeh, Ali Kadkhodaie, Mohammad Hassanpour Sedghi, Hamed Gholami VijouyehContact information: Ali Gholami Vijouyeh, Earth Sciences Department, Faculty of Natural Science, University of Tabriz, Tabriz, Iran, ali.gholami92@ms.tabrizu.ac.ir---------------------------------------------------------------------------------------------Version: 2.0Date of Release: 2023/09/11Identifier: doi: 10.17632/35th6nxwdh.2Permalink: http://dx.doi.org/10.17632/35th6nxwdh.2----------------------------------------------------------------------------------------------------------License:Copyright 2023 Ali Gholami VijouyehPermission is hereby granted only for academic purposes (no permission is required), to any person obtaining a copy of these codes (Software) and associated documentation files in this repository (the "Software"), to deal in the Software codes without restriction.For business and commercial purposes, a written permission from the authors is needed. Please contact the email bellow in order to get permission to use the codes and data for commercial and/or industrial [email protected] DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV
Acanthogyrus (Acanthosentis) barmeshoori Amin, Gholami, Akhlaghi & Heckman 2013
No full textAcanthogyrus (Acanthosentis) barmeshoori Amin, Gholami, Akhlaghi & Heckman, 2013 Host: Aphanius farsicus Locality: Maharlou Lake, Fars Province (Amin et al. 2013 a)Published as part of Tavakol, Sareh, Amin, Omar M., Luus-Powell, Wilmien J. & Halajian, Ali, 2015, The acanthocephalan fauna of Iran, a check list, pp. 237-258 in Zootaxa 4033 (2) on page 241, DOI: 10.11646/zootaxa.4033.2.3, http://zenodo.org/record/23377
A hybrid Python approach to assess microscale human thermal stress in urban environments
No full textMicroclimate simulations are in high demand to assess the thermal impacts of urban design and vegetation changes. Modeling accurate microclimate dynamics in complex urban settings requires extensive computing power. A hybrid Python approach is introduced to simulate human thermal exposure (mean radiant temperature, MRT) and comfort (Universal Thermal Climate Index, UTCI) in cities. The proposed model combines various engines in Rhinoceros to account for interactions between urban surfaces, tree canopies, and the atmosphere. The model was validated in hot, dry Tempe, USA, using in-situ human-biometeorological observations and then applied to urban archetypes in Bologna and Imola, Italy. MRT and UTCI were simulated at five sites in Bologna, four in Imola, and four in Tempe, with varying building heights and canopy cover for the climatologically hottest week of the year (August 3-9). The model performed well with an RMSE of 5.4 degrees C, an index of agreement of 0.96, and outperformed existing models for tree-shaded sites. MRT and UTCI were driven mainly by shade from dense urban forms and trees. Highrise, medium-to-high tree canopy cover archetypes were the coolest concerning thermal exposure and comfort. Sites in Tempe exceeded the UTCI categories for Very Strong or Extreme Heat Stress independent of archetype. The model enables fast and accurate assessment of urban tree planting strategies
Developing a 3D City Digital Twin: Enhancing Walkability through a Green Pedestrian Network (GPN) in the City of Imola, Italy
No full textPredominantly, dense historical cities face insufficient pedestrian-level greenery in the
urban spaces. The lack of greenery impacts the human thermal comfort on the walking paths, which
contributes to a considerable reduction in pedestrian flow rate. This study aims at developing a model
to assess pedestrian-level thermal comfort in city environments and then evaluate the feasibility of
creating a green pedestrian network (GPN). Imola, as a historical city in Italy with a compact urban
pattern, is selected as the case study of this paper. To accomplish this, a three-dimensional digital
twin at city scale is developed for the recognition of real-time shade patterns and for designing a
GPN in this city. The 3D model of the proposed digital twin is developed in the Rhinoceros platform,
and the physiological equivalence temperature (PET) is simulated through EnergyPlus, Honeybee,
and Ladybug components in grasshopper. This study provides the city with a digital twin that is
capable of examining pedestrian-level thermal comfort for designing a GPN based on real-time PET
in the compact urban morphology of Imola. The PET model indicates that during the hottest hour
of the 25th of June, pedestrians in open spaces can experience 3 C more than on narrow shaded
streets. The results are validated based on in situ datasets that prove the reliability of the developed
digital twin for the GPN. It provides urban planners and policy makers with a precise and useful
methodology for simulating the effects of pedestrian-level urban greenery on human thermal comfort
and also guarantees the functionality of policies in different urban settings
Robust distributed secondary voltage restoration control of ac microgrids under multiple communication delays
No full textThis paper focuses on the robust distributed secondary voltage restoration control of AC microgrids (MGs) under multiple communication delays and nonlinear model uncertainties. The problem is addressed in a multi-agent fashion where the generators’ local controllers play the role of cooperative agents communicating over a network and where electrical couplings among generators are interpreted as disturbances to be rejected. Communications are considered to be affected by heterogeneous network-induced time-varying delays with given upper-bounds and the MG is subjected to nonlinear model uncertainties and abrupt changes in the operating working condition. Robustness against uncertainties is achieved by means of an integral sliding mode control term embedded in the control protocol. Then, the global voltage restoration stability, despite the communication delays, is demonstrated through a Lyapunov-Krasovskii analysis. Given the delays’ bounds, and because the resulting stability conditions result in being non-convex with respect to the controller gain, then a relaxed linear matrix inequalities-based tuning criteria is developed to maximize the controller tuning, thus minimizing the restoration settling-time. By means of that, a criteria to estimate the maximal delay margin tolerated by the system is also provided. Finally, simulations on a faithful nonlinear MG model, showing the effectiveness of the proposed control strategy, are further discussed
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