Article
Economics
Muqing Du, Anthony Chen
Summary: Systematic uncertainty analysis is crucial for evaluating the variation in model outputs and identifying critical sources of uncertainty to enhance the reliability and stability of a system. This study presents a sensitivity-based uncertainty analysis approach in equilibrium transit systems, considering uncertainties caused by probabilistic travel demand, congestion, and vehicle frequencies. The proposed method incorporates the congestion effect in passengers' route-choice models and utilizes the hyperpath concept to handle the common-line problem at transit stops. The developed approach enables the simultaneous propagation of uncertainties from different input sources to the model outputs, contributing to the practical applications of sensitivity and uncertainty analyses.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Chemistry, Physical
Jonghyuk Im, Kyungryun Lee, Sohyun Jung, Eunhee Kim, Jung Ho Lee
Summary: A newly proposed method using pre-homonuclear decoupling (PHD) applied to TROSY technique enhances the accuracy and resolution of NMR data analysis by labeling the longitudinal spin order of an a proton on multiple quantum coherences. This approach successfully achieved complete backbone resonance assignment of Tau and alpha-Syn proteins, demonstrating ultrahigh resolution in both amide proton and nitrogen dimensions.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2021)
Article
Management
Elad Michael, Tony A. Wood, Chris Manzie, Iman Shames
Summary: In assignment problems, decision makers are interested in both the optimal assignment and the sensitivity of the optimal assignment to perturbations in the assignment weights. A novel extension of traditional sensitivity analysis is presented in the article, allowing for simultaneous variations in all assignment weights. Two methods of quantifying the sensitivity of the optimal assignment for the bottleneck assignment problem are provided, along with algorithms and numerical examples.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Mathematics, Interdisciplinary Applications
Zahid Khan, Afrah Al-Bossly, Mohammed M. A. Almazah, Fuad S. Alduais
Summary: This paper introduces the concept of neutrosophic gamma distribution (NGD) to address the inadequacy of existing gamma distribution in dealing with uncertain data. The NGD shows better flexibility in handling real data and is suitable for situations with inadequate or ambiguous knowledge.
Article
Engineering, Mechanical
Jiannan Yang
Summary: Probabilistic sensitivity analysis is used to identify influential uncertain inputs for decision-making. A general sensitivity framework is proposed, which unifies various sensitivity measures, including Fisher information. The framework is derived analytically and the sensitivity analysis is reformulated as an eigenvalue problem. The implementation of the framework involves two main steps: Monte Carlo type sampling and solving an eigenvalue equation. The resulting eigenvectors guide the simultaneous variations of input parameters and focus on perturbing uncertainty. The framework is conceptually simple and provides new sensitivity insights for applied mechanics problems.
PROBABILISTIC ENGINEERING MECHANICS
(2023)
Article
Chemistry, Physical
Buddhi Wimarshana, Izzuan Bin-Mat-Arishad, Ashley Fly
Summary: Physico-chemical battery models are capable of simulating lithium-ion cell behavior more accurately by using a more physically descriptive modeling approach. This study demonstrates an improvement in parameter identification accuracy by analyzing the sensitivity of both discharge voltage and EIS data. Different parameters show different sensitivity patterns, and the introduction of non-dimensional EIS spectra states allows for accurate identification of impedance-based parameter sensitivities.
JOURNAL OF POWER SOURCES
(2022)
Article
Engineering, Electrical & Electronic
Ketian Ye, Junbo Zhao, Fei Ding, Rui Yang, Xiao Chen, George W. Dobbins
Summary: This paper proposes a data-driven GSA method for large-scale distribution systems, using deep Gaussian process to identify the mapping relationship between uncertain power injections and voltages, with much better scalability.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Chemistry, Organic
Maria Marta Zanardi, Ariel M. Sarotti
Summary: The study examined the sensitivity of DP4+ when using improper parameter sets, and proposed a customizable methodology for preliminary calculations at any desired level of theory.
JOURNAL OF ORGANIC CHEMISTRY
(2021)
Article
Engineering, Multidisciplinary
Jiannan Yang, Arnau Clot, Robin S. Langley
Summary: Sensitivity analysis is a key step in the design process, which identifies influential parameters. In reliability-based design, the probability of failure mode and its sensitivity to input uncertainties are obtained in a single Monte Carlo simulation using the Likelihood Ratio method. For correlated multiple failure modes, a sensitivity matrix is proposed to guide resource allocation and reduce uncertainties for system reliabilities.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Mechanical
Qing Guo, Hongbo Zhai, Bingbing Suo, Weicheng Zhao, Yongshou Liu
Summary: This paper proposes a novel failure probability-based global sensitivity index by introducing the Bayes formula into the moment-independent global sensitivity index. It estimates the effect of uncertain inputs on the time-variant reliability by comparing the difference between the unconditional probability density function and the conditional probability density function in failure state of input variables. The computational efficiency is improved using a single-loop active learning Kriging method combined with metamodel-based importance sampling. The accuracy of the results obtained by Kriging model is verified by Monte Carlo simulation.
PROBABILISTIC ENGINEERING MECHANICS
(2023)
Article
Geochemistry & Geophysics
Xudong Jiang, Junxing Cao, Jinhai Yang, Jie Liu, Peng Zhou
Summary: This letter proposes an improved AVO attribute analysis method combined with the Teager-Kaiser energy methods for hydrocarbon detection. It has a stronger ability to reveal subtle amplitude anomaly changes caused by hydrocarbons compared to traditional AVO analysis methods. The proposed method enhances the hydrocarbons' characteristics in the prestack gathers using the TKEO algorithm and efficiently highlights the AVO feature by calculating the energy interaction between traces using the CTKEO algorithm. The intercept and gradient product parameters obtained through AVO analysis are used for hydrocarbon detection.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Multidisciplinary Sciences
Sanaa Al-Marzouki, Farrukh Jamal, Christophe Chesneau, Mohammed Elgarhy
Summary: The paper introduces a new three-parameter extended inverse Lomax distribution called the half logistic inverse Lomax distribution and highlights its superiority over the inverse Lomax distribution through various theoretical and practical approaches, including stochastic orders, quantiles, moments, incomplete moments, entropy (Renyi and q), and order statistics. The focus is also placed on parameter estimation and comparison of performance.
Article
Green & Sustainable Science & Technology
Hui Gu, Xiaobo Cui, Hongxia Zhu, Fengqi Si, Yu Kong
Summary: The gas-steam combined cycle, widely used for higher efficiency and lower emissions, is analyzed in this paper for exergy efficiency on each equipment and optimization of the total cost model with three related models as objective functions. A set of Pareto frontier solutions is obtained using NSGA II genetic algorithm, providing operation guidance for high efficiency, low cost, and low emissions.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Automation & Control Systems
Ayush Pandey, Richard M. Murray
Summary: This research focuses on the robustness analysis in model reduction, which is particularly relevant for engineered biological systems. By providing robustness guarantees under parametric uncertainties, an automated model reduction method is proposed to determine the best possible reduced model for a given system model.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Energy & Fuels
Xian -min Zhang, Bai-yan-yue Chen, Zhuang-zhuang Zheng, Qi-hong Feng, Bin Fan
Summary: A theoretical forecasting model based on the generalized Gamma distribution is proposed for estimating gas production in unconventional reservoirs. The model outperforms traditional methods such as Arps and Duong models.
Article
Engineering, Civil
Huthaifa Ashqar, Mohammed Elhenawy, Hesham A. Rakha, Leanna House
Summary: Bike sharing systems are an important part of urban mobility, and the traditional measure of service quality lacks spatial correlation and discrimination between stations. Therefore, this study proposes a new measure called Optimal Occupancy, which takes into account the temporal variations and spatial dependencies of individual stations and provides better prediction of service quality at nearby locations.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Ahmed A. Hussein, Hesham A. Rakha
Summary: This paper develops models to investigate the impact of vehicle position and distance gap on the drag coefficient. The results demonstrate that different vehicle gaps can significantly reduce fuel consumption.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Computer Science, Software Engineering
Hao Chen, Qi Han, Qiong Li, Xiaojun Tong
Summary: This paper proposes a blind detection model for image forensics based on weak feature extraction, which can detect unnatural features in images with a wide detection range and good accuracy. The model utilizes artificial neural networks and feature extraction methods to extract weak features from images, and uses convolution and deep residual networks for feature extraction. The final judgment is made through feature classification networks and a target regression network.
Article
Engineering, Civil
Kyoungho Ahn, Jianhe Du, Mohamed Farag, Hesham A. Rakha
Summary: The paper evaluates the effectiveness of an Eco-Cooperative Automated Control (Eco-CAC) system on a large-scale network in reducing fuel and energy consumption, travel time, and delays. Results show that the system is effective in heavily congested conditions, but the outcomes vary depending on different vehicle compositions and traffic conditions.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Environmental Sciences
Asmaa Alazmi, Hesham Rakha
Summary: This study compared the performance differences between long-term and short-term models in predicting pollutant concentrations and explored the reliability of machine learning models using unrefined mobile measurement data. The results showed that the model based on unrefined data could identify pollutant hot spot areas with similar accuracy compared to the aggregated model. Furthermore, the performance improved when temporal data was added to the model.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Energy & Fuels
Salah A. M. Elmoselhy, Waleed F. Faris, Hesham A. Rakha
Summary: This study analyzes the nonlinearity of the crankshaft in diesel engines and establishes an analytical model for the effect of eccentricity on flexible crankshaft and piston secondary motion. The study finds that the dynamic displacement of the center of the crankshaft is sensitive to changes in its independent variables, with the natural frequency and eccentricity of the crankshaft being the most influential parameters. The developed models are validated with case studies, showing small relative errors. Additionally, the study proposes methods for fatigue failure analysis and improvement of crankshaft performance using nanostructures.
Article
Economics
Javier Bas, Jose L. Zofio, Cinzia Cirillo, Hao Chen, Hesham A. Rakha
Summary: The study explores the potential market share of the Eco-Cooperative Adaptive Cruise Control (Eco-CACC) using a stated choice experiment and models of discrete choice. The results show that potential purchasers consider the trade-off between system cost and fuel savings, with electric vehicle purchasers being less favorable due to the lower cost of electricity. However, there is a significant market share for alternatives that include the Eco-CACC, suggesting a positive attitude towards environmentally friendly technological innovations.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2022)
Article
Green & Sustainable Science & Technology
Mubarak Alrumaidhi, Hesham A. Rakha
Summary: This study modeled the crash severity of elderly drivers using data from Virginia, and found that crashes on two-way roads, involvement of older, distracted, and/or drowsy drivers, unbelted drivers, and high-speed violations are associated with more severe crashes. Crashes involving animals tend to result in property damage only.
Review
Engineering, Industrial
Ammar Sohail, Muhammad Aamir Cheema, Mohammed Eunus Ali, Adel N. Toosi, Hesham A. Rakha
Summary: Road crashes cause significant loss of lives, prompting researchers and transport engineers to focus on data-driven approaches to improve road safety. This study reviews 70 relevant articles, categorizing data sources, equipment, sensors, and analysis methodologies used in data-driven road safety research, highlighting future directions and challenges, such as data collection, poor data quality, and lack of ground truth data.
Article
Energy & Fuels
Kyoungho Ahn, Ahmed Aredah, Hesham A. Rakha, Tongchuan Wei, H. Christopher Frey
Summary: This paper introduces a simple diesel train energy consumption model based on vehicle operational input variables, which can be easily obtained from GPS loggers. The model was tested against real-world data and showed good accuracy, with a total error of -1.33% for all data and varying errors for different train datasets. The study also validated the model with separate data, yielding a relative error of -1.55% for total energy consumption. The proposed model can be useful for evaluating energy consumption effects and conducting train simulations in transportation planning.
Article
Chemistry, Analytical
Mohamed M. G. Farag, Hesham A. Rakha
Summary: Cellular vehicle-to-everything (C-V2X) is a communication technology that supports various applications in safety, mobility, and environment, characterized by higher reliability compared to other technologies. The performance of C-V2X-enabled intelligent transportation system (ITS) applications is influenced by the C-V2X communication technology (mainly packet loss), while the communication performance is affected by the vehicular traffic density, which is determined by traffic mobility patterns and vehicle routing strategies.
Article
Engineering, Civil
Amr K. Shafik, Seifeldeen Eteifa, Hesham A. Rakha
Summary: This paper introduces a robust green light optimal speed advisory (GLOSA) system that considers a probability distribution. The system finds the least-cost vehicle trajectory using a computationally efficient algorithm and dynamic programming to minimize fuel consumption while ensuring safety and passenger comfort. Simulation results show significant fuel savings compared to uninformed driver behavior, and a sensitivity analysis demonstrates the required levels of confidence in predictive timing accuracy to achieve optimal fuel consumption.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Mujahid I. Ashqer, Huthaifa I. Ashqar, Mohammed Elhenawy, Hesham A. Rakha, Marwan Bikdash
Summary: This study introduces a novel approach using probe vehicle data for traffic density estimation, and validates it using datasets from intersections in Greece and Germany. The results show that even with low market penetration rate, relying solely on probe vehicle data can effectively predict traffic density, and having signal phase and timing information is not necessarily important for accuracy.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Proceedings Paper
Hao Chen, Hesham A. Rakha
Summary: This paper integrates an Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I) controller with a multi-objective dynamic router and tests it on a large-scale metropolitan network. The test results demonstrate that the integrated controller improves system-level performance by reducing energy consumption and delays.
2022 IEEE INTERNATIONAL CONFERENCE ON SMART MOBILITY (ICSM 2022)
(2022)
Article
Energy & Fuels
Kyoungho Ahn, Hesham A. Rakha
Summary: This paper presents a simple energy consumption model for hydrogen fuel cell vehicles. The model accurately estimates energy consumption using input variables such as vehicle speed, acceleration, and roadway grade. It can be used by transportation engineers, policy makers, automakers, and environmental engineers to evaluate the energy consumption effects of transportation projects and connected and automated vehicle (CAV) transportation applications within microscopic traffic simulation models.
