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arXiv 2024年

作者： Le, Viet-Anh Malikopoulos, Andreas A. Department of Mechanical Engineering University of Delaware NewarkDE19716 United States Systems Engineering Field Cornell University IthacaNY14850 United States School of Civil and Environmental Engineering Cornell University IthacaNY14853 United States

In this work, we propose a framework for adapting the controller’s parameters based on learning optimal solutions from contextual black-box optimization problems. We consider a class of control design problems for dynamical systems operating in different environments or conditions represented by contextual parameters. The overarching goal is to identify the controller parameters that maximize the controlled system’s performance, given different realizations of the contextual parameters. We formulate a contextual Bayesian optimization problem in which the solution is actively learned using Gaussian processes to approximate the controller adaptation strategy. We demonstrate the efficacy of the proposed framework with a sim-to-real example. We learn the optimal weighting strategy of a model predictive control for connected and automated vehicles interacting with human-driven vehicles from simulations and then deploy it in a real-time experiment. Copyright © 2024, The Authors. All rights reserved.

关键词： Predictive control systems

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Efficient Brillouin frequency shift extraction method employing Brillouin gain spectrum fitting in the distributed BOTDA fiber sensor

Efficient Brillouin frequency shift extraction method employ...

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International Conference on Photonics (ICP)

作者： Abdulwahhab Essa Hamzah Mustafa Essa Hamzah Intan Fatimah Sasila Ghadzali Mahmoud Muhanad Fadhel Nurfarhana Mohamad Sapiee Mohd Saiful Dzulkefly Zan Yosuke Tanaka Hisham Mohamad Sawal Hamid Md Ali Ahmad Ashrif A Bakar Department of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Bangi Selangor Malaysia Division of Advanced Electrical and Electronic Engineering Institute of Engineering Tokyo University of Agriculture and Technology Japan Civil & Environmental Engineering Department Universiti Teknologi PETRONAS Seri Iskandar Perak Malaysia

ISBN: (数字)9798350383164

ISBN: (纸本)9798350383171

This paper demonstrates the deployment of quadratic curve fitting (QCF) based on half-peak Brillouin gain spectrum (BGS) for fast and accurate Brillouin frequency shift (BFS) extraction. The method was analysed and compared with three other methods such as Lorentzian curve fitting (LCF), Gaussian curve fitting (GCF) and pseudo-Voigt curve fitting (pVCF). The QCF based on half-peak achieved an accuracy similar to other curve fitting methods. In addition, the QCF has a faster processing time by eight-fold than the others, allowing the system to handle a large amount of data with good performance. The results would provide some general ideas for deploying the QCF algorithm for the system on chip platform with direct detection for fast BFS measurement.

关键词： Semiconductor device measurement Optical fiber sensors Accuracy Fitting Scattering System-on-chip Velocity measurement Curve fitting Photonics

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Using statewide transportation planning model to forecast demand for electric vehicle charging at stations along intercity highways

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International Journal of Transportation Science and Technology 2024年

作者： Cruz, Michael Yahyazadeh Rineh, Ehsan Alberto Luna Fong, Sergio Long Cheu, Ruey Song, Ziqi Department of Aerospace & Mechanical Engineering The University of Texas at El Paso El PasoTX United States Department of Civil Engineering The University of Texas at El Paso El PasoTX United States Department of Industrial Manufacturing & Systems Engineering The University of Texas at El Paso El PasoTX United States Department of Civil Structural & Environmental Engineering University of Buffalo BuffaloNY United States

The availability of Charging Stations (CSs) with adequate capacity is critical for the growth in ownership and usage of Electric Vehicles (EVs). In the United States, the state Departments of Transportation (DOTs) are responsible for planning CSs along the Interstate, national, and state highways. While the state DOTs have their Statewide Transportation Planning Models (STPMs), most of these models do not represent EVs internally. The state DOTs can only rely on the existing STPMs to forecast the demand for EV charging at specific CS locations in a state's highway network. This research proposes a methodology that utilizes an existing STPM, EV and non-EV vehicle registration data, and hourly traffic volumes at strategic counting stations to predict the hourly demand for EV charging (charging port occupancy) at proposed CSs. This approach first estimates the volume of all passenger cars that will pass the vicinity of a CS along intercity highways, and identifies the Traffic Analysis Zones (TAZs) of their trip origins. Based on the EV adoption rates of the TAZs, EV range, and EV owner's charging behavior, the methodology forecasts the volume of EVs that pass the vicinity of a CS and the number of EVs that will stop at the CS to charge every hour of the day. An example problem demonstrated the application of the methodology in the State of Texas. It not only forecasted the hourly occupancy at CSs along three major corridors, but also demonstrated how to determine the capacities of the CSs. The challenges of using the existing STPM and their solutions are discussed. This proposed methodology enables the state DOTs to forecast the demand for EV charging and the capacities at the proposed CSs along intercity highways, thus allowing the DOTs to apply for federal funds to accelerate the deployment of the CSs. © 2024 Tongji University and Tongji University Press

关键词： Electric vehicles

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Characterization of Systematic Bias in ALOS-2 Multilooked Interferograms

Characterization of Systematic Bias in ALOS-2 Multilooked In...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Ryu Sugimoto Yu Morishita Masanobu Shimada Ryo Natsuaki Chiaki Tsutsumi Ryosuke Nakamura Toru Kouyama Digital Architecture Research Center National Institute of Advanced Industrial Science and Technology Japan Division of Architectural Civil and Environmental Engineering School of Science and Engineering Tokyo Denki University Japan Department of Electrical Engineering and Information Systems The University of Tokyo Japan

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Interferometric SAR time series analysis using multilooked interferograms has measured ground deformation with high accuracy over large areas, but is known to be contaminated by a systematic bias when using only short-term interferograms. This bias, also referred to as a "fading signal", has been investigated using the abundant time series data from Sentinel-1 C-band SAR, and soil moisture and biomass changes have been suggested as two possible causes for the observed bias. Several correction methods have been proposed to mitigate the phase bias, assuming a periodic observation strategy. The phase bias is supposed to increase with the wavelength, but the bias in ALOS-2 L-band SAR has not been investigated in detail because the data distribution policy restricts its users. In addition, these correction methods are not suitable for the infrequently observed data such as ALOS-2. In this paper, we investigated the systematic bias in ALOS-2 multilooked interferograms with respect to various interferometric pairs. We also corrected the phase bias using the noise-filtering technique. The bias in ALOS-2 multilooked interferograms showed >3 mm/year with an average temporal baseline of 144 days, which is equivalent to that of Sentinel-1 with the temporal baseline of 78 days. That is, the bias effect toward the temporal baseline was larger in ALOS-2 than in Sentinel-1. The noise-filtering technique could mitigate the bias with less pairs regardless of land-use.

关键词： Fading channels Systematics Soil measurements Time series analysis Soil moisture Sentinel-1 Geoscience and remote sensing

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An Investigation into Upward Tie Movements at Railroad Bridge Approaches in Time and Frequency Domains

SSRN

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SSRN 2023年

作者： Boler, Huseyin Mishra, Debakanta Tutumluer, Erol Sussmann, Theodore R. Civil Engineering Konya Technical University Konya Turkey School of Civil and Environmental Engineering Oklahoma State University United States Department of Civil and Environmental Engineering University of Illinois at Urbana-Champaign United States Volpe National Transportation Systems Center 55 Broadway Kendall Square CambridgeMA02142 United States

This manuscript presents time and frequency domain analyses of transient track displacements recorded under train passage at an instrumented bridge approach. Emphasis has been given to excessive upward tie movements that were recorded at the Near-Bridge Location (NBL), but not at the Open-Track Location (OTL). First, the displacement and acceleration time histories are analyzed in the time domain to identify different events associated with the tie lifting phenomenon. Next, the displacement and acceleration time histories are analyzed in the frequency domain to identify dominant frequencies governing the tie vibration at both NBL as well as OTL. A theoretical approach based on train dimensions and operating speed has been adopted to demarcate the dominant tie vibration frequencies associated with the passage of the train. The field data at NBL is observed to have two additional frequencies, 7.4 Hz and 9.2 Hz, that cannot be accounted for by the theoretical calculations. The upward movement of the tie has been linked to the vibration amplitude at 7.4 Hz. Therefore, the authors have emphasized the importance of combined time- and frequency-domain analysis while studying the transient track deformation trends at bridge approaches. © 2023, The Authors. All rights reserved.

关键词： Bridge approaches

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Distributed Optimization for Traffic Light Control and Connected Automated Vehicle Coordination in Mixed-Traffic Intersections

arXiv

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arXiv 2024年

In this paper, we consider the problem of coordinating traffic light systems and connected automated vehicles (CAVs) in mixed-traffic intersections. We aim to develop an optimization-based control framework that leverages both the coordination capabilities of CAVs at higher penetration rates and intelligent traffic management using traffic lights at lower penetration rates. Since the resulting optimization problem is a multi-agent mixed-integer quadratic program, we propose a penalization-enhanced maximum block improvement algorithm to solve the problem in a distributed manner. The proposed algorithm, under certain mild conditions, yields a feasible person-by-person optimal solution of the centralized problem. The performance of the control framework and the distributed algorithm is validated through simulations across various penetration rates and traffic volumes. Copyright © 2024, The Authors. All rights reserved.

关键词： Quadratic programming

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environmental Life Cycle Assessment of a Novel Offshore Wind Energy Design Project: A United States Based Case Study

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SSRN 2023年

作者： Moussavi, Sussan Barutha, Phillip Dvorak, Bruce Department of Civil and Environmental Engineering University of Nebraska- LincolnNE68588 United States Department of Civil and Environmental Engineering and Earth Sciences University of Notre Dame Notre DameIN46556 United States Department of Biological Systems Engineering University of Nebraska-Lincoln NE68588 United States

Renewable energy resources, particularly offshore wind energy, and their role in combating global climate change have gained significant interest in recent years. Considering the potential life cycle impacts of such systems is essential to support effective policy and decision making. This study used life cycle assessment to compare the environmental sustainability of an offshore wind farm case study employing a novel foundation design to one employing a conventional foundation design. Although literature related to the environmental sustainability of offshore wind facilities exists, these studies have not examined large scale US based facilities using a detailed data inventory from a real case study. The results of this study show that alternative foundation designs can decrease the overall life cycle environmental impact of a large scale offshore wind farm. In general, the proposed novel design is favorable from a life cycle perspective compared to the conventional design, particularly in the impact categories of ecotoxicity, eutrophication, carcinogenics, non-carcinogenics, and respiratory effects. The energy payback time was calculated and found to be less than one year for both designs. Additional benefits of the novel design concept include lower material costs, quicker and easier installation, increased domestic job opportunities, decreased reliance on foreign supply chains, ability to expand the design to deeper and disaster prone waters globally, and increased support for current political goals. Scenario sensitivity analyses showed that the environmental impact of wind energy systems may decrease with domestic sourcing of foundation materials and reuse of the foundation after decommissioning the wind farm. © 2023, The Authors. All rights reserved.

关键词： Life cycle

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A discrete moth-flame optimization algorithm for multiple automated guided vehicles scheduling problem in a matrix manufacturing workshop

A discrete moth-flame optimization algorithm for multiple au...

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作者： Zeng, Junhai Xie, Wei Pan, Mi School of Automation Science and Engineering South China University of Technology Guangdong Guangzhou510641 China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education South China University of Technology Guangdong Guangzhou510641 China Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing South China University of Technology Guangdong Guangzhou510641 China Department of Civil and Environmental Engineering University of Macau 999078 China

The growing need for customized and varied production has highlighted the significance of smart and automated factories in the manufacturing sector. In this particular context, the scheduling of multiple Automated Guided Vehicles (AGVs) plays a pivotal role in enhancing the efficiency of operations within an intelligent manufacturing shop. This study centers on the material handling process within a matrix manufacturing shop with the objective of identifying the most cost-effective transportation routes for materials. To accomplish the specified objective, this research aims to identify an optimal solution for reducing transportation costs. In particular, this study formulates a mixed-integer linear programming model and introduces a novel discrete variant of the moth-flame optimization (MFO) algorithm, named DMFO, to address the scheduling problem. The DMFO algorithm incorporates several significant enhancements. Firstly, a population initialization method is proposed, which combines a nearest-neighbor-based adaptive heuristic and a random sorting technique to ensure the formation of a well-structured population. Secondly, the flame generation mechanism and spiral flight search processes within the MFO have been redefined to achieve a more optimal balance between exploration and exploitation. A neighborhood search mechanism is subsequently devised, employing the concept of neighborhood relevance to accelerate the convergence process. Additionally, a heuristic approach is introduced to reduce the computational cost. Moreover, a population regeneration mechanism is proposed to avoid the algorithm falling into a local optimum. To validate the effectiveness of the DMFO, a comparative analysis is conducted using a dataset of 110 real-world factory instances. In this analysis, eight well-established optimization algorithms are employed. The simulation results consistently demonstrate that the relative percentage deviation (RPD) value of the DMFO tends to approach 0% more

关键词： Materials handling

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Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale

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Geoscience Frontiers 2022年第3期13卷 79-99页

作者： Georgia Papacharalampous Hristos Tyralis Ilias G.Pechlivanidis Salvatore Grimaldi Elena Volpi Department of Engineering Roma Tre UniversityVia V.Volterra 6200146 RomeItaly Department of Water Resources and Environmental Engineering School of Civil EngineeringNational Technical University of AthensHeroon Polytechneiou 515780 ZographouGreece Hellenic Air Force General Staff Hellenic Air ForceMesogion Avenue 227-23115561 CholargosGreece Swedish Meteorological and Hydrological Institute 60176 NorrköpingSweden Department for Innovation in Biological Agro-food and Forest SystemsUniversity of TusciaViterboItaly Department of Mechanical and Aerospace Engineering Tandon School of EngineeringNew York UniversityBrooklynNY10003United States

Statistical analyses and descriptive characterizations are sometimes assumed to be offering information on time series *** the scientific interest suggested by such assumptions,the relationships between descriptive time series features(e.g.,temporal dependence,entropy,seasonality,trend and linearity features)and actual time series forecastability(quantified by issuing and assessing forecasts for the past)are scarcely studied and quantified in the *** this work,we aim to fill in this gap by investigating such relationships,and the way that they can be exploited for understanding hydroclimatic forecastability and its *** this end,we follow a systematic framework bringing together a variety of–mostly new for hydrology–concepts and methods,including 57 descriptive features and nine seasonal time series forecasting methods(i.e.,one simple,five exponential smoothing,two state space and one automated autoregressive fractionally integrated moving average methods).We apply this framework to three global datasets originating from the larger Global Historical Climatology Network(GHCN)and Global Streamflow Indices and Metadata(GSIM)*** these datasets comprise over 13,000 monthly temperature,precipitation and river flow time series from several continents and hydroclimatic regimes,they allow us to provide trustable characterizations and interpretations of 12-month ahead hydroclimatic forecastability at the global *** first find that the exponential smoothing and state space methods for time series forecasting are rather equally efficient in identifying an upper limit of this forecastability in terms of Nash-Sutcliffe efficiency,while the simple method is shown to be mostly useful in identifying its lower *** then demonstrate that the assessed forecastability is strongly related to several descriptive features,including seasonality,entropy,(partial)autocorrelation,stability,(non)linearity,spikiness and heterogeneity features

关键词： Exponential smoothing Predictability Statistical hydrology Time series analysis Time series clustering Time series forecasting

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Towards Near Real-time Digital Twins of Construction Sites: Developing High LOD 4D Simulation Based on Computer Vision and RTLS 38

Towards Near Real-time Digital Twins of Construction Sites: ...

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38th International Symposium on Automation and Robotics in Construction, ISARC 2021

作者： Huang, Yusheng Hammad, Amin Torabi, Ghazaleh Ghelmani, Ali Guevremont, Michel Department of Building Civil and Environmental Engineering Concordia University Canada Concordia Institute of Information Systems Engineering Concordia University Canada Department of Electrical and Computer Engineering Concordia University Canada

ISBN: (纸本)9789526952413

4D simulation can be used in the planning phase of a project for constructability analysis, which aims to optimize construction processes and improve safety management. The same 4D simulation can be used as a digital twin in the construction phase for progress monitoring and identifying potential safety issues based on micro-schedules. A micro-schedule is a schedule listing tasks of short durations (i.e., days or hours) with the information of the resources assigned to each task (i.e., workers, equipment and materials). The site data can be collected using Computer Vision (CV) or Real-Time Location systems (RTLS) to identify and recognize the activities of construction resources, as well as to capture the progress of the project. This paper aims to explore the possibility of developing near real-time digital twins of construction sites. The digital twin is developed as a high Level of Development (LOD) 4D Simulation based on CV and RTLS data. A case study is performed to investigate the proposed method. © 2021 Proceedings of the International Symposium on Automation and Robotics in Construction. All rights reserved.

关键词： Computer vision

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