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Electrical grounding is an indispensable part of the power system network. The grounding system is mainly affected by grounding resistance and the nature of the soil. High ground resistance produces the phenomenon of soil ionization, surface arching, and back flashover. A conventional grounding system requires the deep digging of electrodes, thus creating maintenance difficulties. This research work focuses on the safe operation of an electric power system from external and internal impulses arising due to lightning strikes or short circuits. The study proposes an application of mineral samples as grounding materials, and bentonite is used as backfilling material in portable grounding systems. A detailed experimental analysis was conducted under controlled conditions to evaluate the performance of selected materials in high-resistance soil. The problem of a deeply driven electrode is addressed by designing the portable grounding system. The study results demonstrate that the proposed portable grounding system could be installed in troubled environments such as forests, deserts, and rocky terrains. To measure the breakdown voltages of the proposed samples, X-ray Diffraction (XRD) analysis and other laboratory tests were conducted. The electric field intensities are extracted through Finite Element Analysis (FEA). The experimental and simulation findings show the expected performance of mineral samples under various operating conditions. The findings of this study can guide the practitioners for safe and efficient operations of portable electrical grounding systems.
Rizwan Ahmad; Mahmoud Kassas; Chokri B. Ahmed; Faisal Khan; Sikandar Khan; Arshad Jamal; Irshad Ullah. Application of Mineral Compounds for a High-Voltage Portable Grounding System: An Experimental Study. Electronics 2021, 10, 2043 .
AMA StyleRizwan Ahmad, Mahmoud Kassas, Chokri B. Ahmed, Faisal Khan, Sikandar Khan, Arshad Jamal, Irshad Ullah. Application of Mineral Compounds for a High-Voltage Portable Grounding System: An Experimental Study. Electronics. 2021; 10 (16):2043.
Chicago/Turabian StyleRizwan Ahmad; Mahmoud Kassas; Chokri B. Ahmed; Faisal Khan; Sikandar Khan; Arshad Jamal; Irshad Ullah. 2021. "Application of Mineral Compounds for a High-Voltage Portable Grounding System: An Experimental Study." Electronics 10, no. 16: 2043.
Crosswalks are critical locations in the urban transport network that need to be designed carefully as pedestrians are directly exposed to vehicular traffic. Although various methods are available to evaluate the level of service (LOS) at pedestrian crossings, pedestrian crossing facilities are frequently ignored in assessing crosswalk conditions. This study attempts to provide a comprehensive framework for evaluating crosswalks based on several essential indicators adopted from different guidelines. A new pedestrian crossing level of service (PCLOS) method is introduced in this research, with an aimto promote safe and sustainable operations at such locations. The new PCLOS employs an analytical point system to compare existing street crossing conditions to the guidelines’ standards, taking into account the scores and coefficients of the indicators. The quantitative scores and coefficients of indicators are assigned based on field observations and respondent opinions. The method was tested to evaluate four pedestrian crosswalks in the city of Putrajaya, Malaysia. A total of 17 indicators were selected for the study after a comprehensive literature review. Survey results show that the provision of a zebra crossing was the most critical indicator at the pedestrian crossings, while drainage near crosswalks was regarded as the least important. Four indicators had a coefficient value above 4, indicating that these are very critical pedestrian crossing facilities and significantly impact the calculation of LOS for pedestrian crossings. Four crosswalks were evaluated using the proposed method in Putrajaya, Malaysia. The crosswalk at the Ministry of Domestic Trade Putrajaya got the “PCLOS A”. In contrast, the midblock crossing in front of the Putrajaya Corporation was graded “PCLOS C”. While the remaining two crosswalks were graded as “PCLOS B” crosswalks. Based on the assigned PCLOS grade, the proposed method could also assist in identifying current design and operation issues in existing pedestrian crossings and providing sound policy recommendations for improvements to ensure pedestrian safety.
Tufail Ahmed; Mehdi Moeinaddini; Meshal Almoshaogeh; Arshad Jamal; Imran Nawaz; Fawaz Alharbi. A New Pedestrian Crossing Level of Service (PCLOS) Method for Promoting Safe Pedestrian Crossing in Urban Areas. International Journal of Environmental Research and Public Health 2021, 18, 8813 .
AMA StyleTufail Ahmed, Mehdi Moeinaddini, Meshal Almoshaogeh, Arshad Jamal, Imran Nawaz, Fawaz Alharbi. A New Pedestrian Crossing Level of Service (PCLOS) Method for Promoting Safe Pedestrian Crossing in Urban Areas. International Journal of Environmental Research and Public Health. 2021; 18 (16):8813.
Chicago/Turabian StyleTufail Ahmed; Mehdi Moeinaddini; Meshal Almoshaogeh; Arshad Jamal; Imran Nawaz; Fawaz Alharbi. 2021. "A New Pedestrian Crossing Level of Service (PCLOS) Method for Promoting Safe Pedestrian Crossing in Urban Areas." International Journal of Environmental Research and Public Health 18, no. 16: 8813.
Saudi Arabia is one of the countries with the highest number of road accidents and associated fatalities in the world. Speeding has been identified as an important cause of increased traffic accidents, which also aggravate their severity. Road safety improvement strategies are primarily based on the accurate identification of accident hotspots. Installing speed cameras at a network level is an expensive road safety measure, and its spatiotemporal effectiveness should be assessed. In this study, a traffic accident risk assessment framework has been developed and implemented on the 84 km long Buraydah Ring Road in the Qassim region of Saudi Arabia. The selected highway was divided into 42 (×2 km long) segments using the ArcGIS software. A risk scoring scheme was developed to incorporate both the frequency and severity of road accidents. Speed cameras installation at various segments showed a 70% decline in total accident counts, 53% in accidents with property damage, 84% decline in accidents causing injury, and complete absence of accidents with fatalities. The 48% segments were identified as hotspots with risk level ≥ medium, while the speed cameras installation completely eliminated the hotspots from the study area. The proposed framework can be implemented on major high-speed highways, accommodating high traffic volumes, for hotspot identification and evaluation of various road safety measures in Saudi Arabia and elsewhere.
Meshal Almoshaogeh; Radfan Abdulrehman; Husnain Haider; Fawaz Alharbi; Arshad Jamal; Saif Alarifi; Shafiquzzaman. Traffic Accident Risk Assessment Framework for Qassim, Saudi Arabia: Evaluating the Impact of Speed Cameras. Applied Sciences 2021, 11, 6682 .
AMA StyleMeshal Almoshaogeh, Radfan Abdulrehman, Husnain Haider, Fawaz Alharbi, Arshad Jamal, Saif Alarifi, Shafiquzzaman. Traffic Accident Risk Assessment Framework for Qassim, Saudi Arabia: Evaluating the Impact of Speed Cameras. Applied Sciences. 2021; 11 (15):6682.
Chicago/Turabian StyleMeshal Almoshaogeh; Radfan Abdulrehman; Husnain Haider; Fawaz Alharbi; Arshad Jamal; Saif Alarifi; Shafiquzzaman. 2021. "Traffic Accident Risk Assessment Framework for Qassim, Saudi Arabia: Evaluating the Impact of Speed Cameras." Applied Sciences 11, no. 15: 6682.
Crash prediction models (CPM) are mostly used for network screening in the road safety management process. The Highway Safety Manual (HSM) offers consistent and reliable CPMs for various roadway facilities that are commonly known as safety performance functions (SPFs). SPFs are statistical regression models that estimate the expected crash frequencies by crash severity, type, and facility types as a function of highway geometric characteristics and traffic exposure. They are vital in identifying high-frequency crash locations and assessing the effectiveness of safety countermeasures. HSM SPFs were originally developed using data collected from a selected few states in the USA. When applied to different jurisdictions, agencies can either develop local SPFs or calibrate the existing HSM base SPFs for local conditions depending on various trade-offs. This study aims to calibrate HSM-default SPFs for multilanes rural divided highway segments using three years of crash data (2017–2019) in the Kingdom of Saudi Arabia (KSA). In this regard, two highways (NHWY-80 and NHWY-85) in the eastern region were considered for the analysis. Crash and traffic data were procured from the MOT (Ministry of Transport), Riyadh, KSA. Geometric data was collected from MOT as well as google earth and field surveys. Calibration procedure as recommended by HSM was followed to obtain the local calibration factors. The Interactive Highway Safety Design Model (IHSDM) calibrator tool was used for the analysis. SPFs calibration results revealed that HSM predictive methodology consistently overpredicts all types of crashes (i.e., total, fatal and injury, and property damage crashes) on both highways. The estimated calibration factors ranged from 0.53 to 0.78. Various goodness of fit (GOF) measures (like MAD, MSPE, MPB) were used for quality assessment of calibrated SPFs. Methods used in this study could be beneficially practiced in any jurisdiction. Calibrated SPFs provide a favorable alternative and replacement of HSM-default SPFs, thereby making the crash predictions more accurate and thus helps in better decision-making related to highway safety.
Hassan M. Al-Ahmadi; Arshad Jamal; Tufail Ahmed; Muhammad Tauhidur Rahman; Imran Reza; Danish Farooq. Calibrating the Highway Safety Manual Predictive Models for Multilane Rural Highway Segments in Saudi Arabia. Arabian Journal for Science and Engineering 2021, 1 -15.
AMA StyleHassan M. Al-Ahmadi, Arshad Jamal, Tufail Ahmed, Muhammad Tauhidur Rahman, Imran Reza, Danish Farooq. Calibrating the Highway Safety Manual Predictive Models for Multilane Rural Highway Segments in Saudi Arabia. Arabian Journal for Science and Engineering. 2021; ():1-15.
Chicago/Turabian StyleHassan M. Al-Ahmadi; Arshad Jamal; Tufail Ahmed; Muhammad Tauhidur Rahman; Imran Reza; Danish Farooq. 2021. "Calibrating the Highway Safety Manual Predictive Models for Multilane Rural Highway Segments in Saudi Arabia." Arabian Journal for Science and Engineering , no. : 1-15.
A paradigm shift in power engineering transforms conventional fossil fuel-based power systems gradually into more sustainable and environmentally friendly systems due to more renewable energy source (RES) integration. However, the control structure of high-level RES integrated system becomes complex, and the total system inertia is reduced due to the removal of conventional synchronous generators. Thus, such a system poses serious frequency instabilities due to the high rate of change of frequency (RoCoF). To handle this frequency instability issue, this work proposes an optimized fractional-order proportional integral (FOPI) controller-based superconducting magnetic energy storage (SMES) approach. The proposed FOPI-based SMES technique to support virtual inertia is superior to and more robust than the conventional technique. The FOPI parameters are optimized using the particle swarm optimization (PSO) technique. The SMES is modeled and integrated into the optimally designed FOPI to support the virtual inertia of the system. Fluctuating RESs are considered to show the effectiveness of the proposed approach. Extensive time-domain simulations were carried out in MATLAB Simulink with different load and generation mismatch levels. Systems with different inertia levels were simulated to guarantee the frequency stability of the system with the proposed FOPI-based SMES control technique. Several performance indices, such as overshoot, undershoot, and settling time, were considered in the analysis.
Shafiul Alam; Fahad Al-Ismail; Mohammad Abido. PV/Wind-Integrated Low-Inertia System Frequency Control: PSO-Optimized Fractional-Order PI-Based SMES Approach. Sustainability 2021, 13, 7622 .
AMA StyleShafiul Alam, Fahad Al-Ismail, Mohammad Abido. PV/Wind-Integrated Low-Inertia System Frequency Control: PSO-Optimized Fractional-Order PI-Based SMES Approach. Sustainability. 2021; 13 (14):7622.
Chicago/Turabian StyleShafiul Alam; Fahad Al-Ismail; Mohammad Abido. 2021. "PV/Wind-Integrated Low-Inertia System Frequency Control: PSO-Optimized Fractional-Order PI-Based SMES Approach." Sustainability 13, no. 14: 7622.
Electrical energy and power demand will experience exponential increase with the rise of the global population. Power demand is predictable and can be estimated based on population and available historical data. However, renewable energy sources (RES) are intermittent, unpredictable, and environment-dependent. Interestingly, microgrids are becoming smarter but require adequate and an appropriate energy storage system (ESS) to support their smooth and optimal operation. The deep discharge caused by the charging–discharging operation of the ESS affects its state of health, depth of discharge (DOD), and life cycle, and inadvertently reduces its lifetime. Additionally, these parameters of the ESS are directly affected by the varying demand and intermittency of RES. This study presents an assessment of battery energy storage in wind-penetrated microgrids considering the DOD of the ESS. The study investigates two scenarios: a standalone microgrid, and a grid-connected microgrid. The problem is formulated based on the operation cost of the microgrid considering the DOD and the lifetime of the battery. The optimization problem is solved using non-linear programming. The scheduled operation cost of the microgrid, the daily scheduling cost of ESS, the power dispatch by distributed generators, and the DOD of the battery storage at any point in time are reported. Performance analysis showed that a power loss probability of less than 10% is achievable in all scenarios, demonstrating the effectiveness of the study.
Umar Salman; Khalid Khan; Fahad Alismail; Muhammad Khalid. Techno-Economic Assessment and Operational Planning of Wind-Battery Distributed Renewable Generation System. Sustainability 2021, 13, 6776 .
AMA StyleUmar Salman, Khalid Khan, Fahad Alismail, Muhammad Khalid. Techno-Economic Assessment and Operational Planning of Wind-Battery Distributed Renewable Generation System. Sustainability. 2021; 13 (12):6776.
Chicago/Turabian StyleUmar Salman; Khalid Khan; Fahad Alismail; Muhammad Khalid. 2021. "Techno-Economic Assessment and Operational Planning of Wind-Battery Distributed Renewable Generation System." Sustainability 13, no. 12: 6776.
A better understanding of injury severity risk factors is fundamental to improving crash prediction and effective implementation of appropriate mitigation strategies. Traditional statistical models widely used in this regard have predefined correlation and intrinsic assumptions, which, if flouted, may yield biased predictions. The present study investigates the possibility of using the eXtreme Gradient Boosting (XGBoost) model compared with few traditional machine learning algorithms (logistic regression, random forest, and decision tree) for crash injury severity analysis. The data used in this study was obtained from the traffic safety department, ministry of transport (MOT) at Riyadh, KSA, and contains 13,546 motor vehicle collisions along 15 rural highways reported between January 2017 to December 2019. Empirical results obtained using k-fold (k = 10) for various performance metrics showed that the XGBoost technique outperformed other models in terms of the collective predictive performance as well as injury severity individual class accuracies. XGBoost feature importance analysis indicated that collision type, weather status, road surface conditions, on-site damage type, lighting conditions, and vehicle type are the few sensitive variables in predicting the crash injury severity outcome. Finally, a comparative analysis of XGBoost based on different performance statistics showed that our model outperformed most previous studies.
Arshad Jamal; Muhammad Zahid; Muhammad Tauhidur Rahman; Hassan M. Al-Ahmadi; Meshal Almoshaogeh; Danish Farooq; Mahmood Ahmad. Injury severity prediction of traffic crashes with ensemble machine learning techniques: a comparative study. International Journal of Injury Control and Safety Promotion 2021, 1 -20.
AMA StyleArshad Jamal, Muhammad Zahid, Muhammad Tauhidur Rahman, Hassan M. Al-Ahmadi, Meshal Almoshaogeh, Danish Farooq, Mahmood Ahmad. Injury severity prediction of traffic crashes with ensemble machine learning techniques: a comparative study. International Journal of Injury Control and Safety Promotion. 2021; ():1-20.
Chicago/Turabian StyleArshad Jamal; Muhammad Zahid; Muhammad Tauhidur Rahman; Hassan M. Al-Ahmadi; Meshal Almoshaogeh; Danish Farooq; Mahmood Ahmad. 2021. "Injury severity prediction of traffic crashes with ensemble machine learning techniques: a comparative study." International Journal of Injury Control and Safety Promotion , no. : 1-20.
Integration of renewable energy sources (RES) in a distribution network facilities the establishment of sustainable power systems. Concurrently, the incorporation of energy storage system (ESS) plays a pivotal role to maintain the economical significance as well as mitigates the technical liabilities associated with uncontrollable and fluctuating renewable output power. Nevertheless, ESS technologies require additional investments that imposes a techno-economic challenge of selection, allocation and sizing to ensure a reliable power system that is operationally optimized with reduced cost. In this paper, a deterministic cost-optimization framework is presented based on a multi-input nonlinear programming to optimally solve the sizing and allocation problem. The optimization is performed to obviate the demand-generation mismatch, that is violated with the introduction of variable renewable energy sources. The proposed optimization method is tested and validated on an IEEE 24-bus network integrated with solar and wind energy sources. The deterministic approach is solved using GAMS optimization software considering the system data of one year. Based on the optimization framework, the study also presents various different scenarios of renewable energy mix in combination with advanced ESS technologies to outline an technical as well as economical framework for ESS sizing, allocation, and selection. Based on the optimal results obtained, the optimal sizing and allocation were obtained for lead-acid, lithium-ion, nickel-cadmium and sodium-sulfur (NaS) battery energy storage system. While all these storage technologies mitigated the demand-generation mismatch with optimal size and location. However, the NaS storage technology was found to be the best among the given storage technologies for the given system minimum possible cost. Furthermore, it was observed that the cost of hybrid wind-solar mix system results in the lowest overall cost.
Yousef Alhumaid; Khalid Khan; Fahad Alismail; Muhammad Khalid. Multi-Input Nonlinear Programming Based Deterministic Optimization Framework for Evaluating Microgrids with Optimal Renewable-Storage Energy Mix. Sustainability 2021, 13, 5878 .
AMA StyleYousef Alhumaid, Khalid Khan, Fahad Alismail, Muhammad Khalid. Multi-Input Nonlinear Programming Based Deterministic Optimization Framework for Evaluating Microgrids with Optimal Renewable-Storage Energy Mix. Sustainability. 2021; 13 (11):5878.
Chicago/Turabian StyleYousef Alhumaid; Khalid Khan; Fahad Alismail; Muhammad Khalid. 2021. "Multi-Input Nonlinear Programming Based Deterministic Optimization Framework for Evaluating Microgrids with Optimal Renewable-Storage Energy Mix." Sustainability 13, no. 11: 5878.
The potential effects of autonomous vehicles (AVs) on greenhouse gas (GHG) emissions are uncertain, although numerous studies have been conducted to evaluate the impact. This paper aims to synthesize and review all the literature regarding the topic in a systematic manner to eliminate the bias and provide an overall insight, while incorporating some statistical analysis to provide an interval estimate of these studies. This paper addressed the effect of the positive and negative impacts reported in the literature in two categories of AVs: partial automation and full automation. The positive impacts represented in AVs’ possibility to reduce GHG emission can be attributed to some factors, including eco-driving, eco traffic signal, platooning, and less hunting for parking. The increase in vehicle mile travel (VMT) due to (i) modal shift to AVs by captive passengers, including elderly and disabled people and (ii) easier travel compared to other modes will contribute to raising the GHG emissions. The result shows that eco-driving and platooning have the most significant contribution to reducing GHG emissions by 35%. On the other side, easier travel and faster travel significantly contribute to the increase of GHG emissions by 41.24%. Study findings reveal that the positive emission changes may not be realized at a lower AV penetration rate, where the maximum emission reduction might take place within 60–80% of AV penetration into the network.
Moneim Massar; Imran Reza; Syed Rahman; Sheikh Abdullah; Arshad Jamal; Fahad Al-Ismail. Impacts of Autonomous Vehicles on Greenhouse Gas Emissions—Positive or Negative? International Journal of Environmental Research and Public Health 2021, 18, 5567 .
AMA StyleMoneim Massar, Imran Reza, Syed Rahman, Sheikh Abdullah, Arshad Jamal, Fahad Al-Ismail. Impacts of Autonomous Vehicles on Greenhouse Gas Emissions—Positive or Negative? International Journal of Environmental Research and Public Health. 2021; 18 (11):5567.
Chicago/Turabian StyleMoneim Massar; Imran Reza; Syed Rahman; Sheikh Abdullah; Arshad Jamal; Fahad Al-Ismail. 2021. "Impacts of Autonomous Vehicles on Greenhouse Gas Emissions—Positive or Negative?" International Journal of Environmental Research and Public Health 18, no. 11: 5567.
The energy storage devices and renewable energy integration have great impacts on modern power system. The optimal site selection and network expansion under several uncertainties, however, are the challenging tasks in modern interconnected power system. This paper proposes a robust optimal planning strategy to find the location and the size of the energy storage system (ESS) among the power network buses and transmission lines expansion to accommodate the wind power energy integration to serve the future demand growth under uncertainties. The proposed methodology provides the optimal location concerning the required size of ESS at each bus, along with the optimal selections to reinforce existing lines or recommending new ones in a single solving stage. The co-optimization problem is formulated as a mixed-integer linear programming problem, in which the power balance constraint is developed as an optimal power flow. The stochastic optimization problem is solved robustly using the chance-constrained method. Furthermore, the load shedding and wind curtailment are taken into account in the cost function. The methodology is tested in the IEEE RTS-96 system. The simulation results demonstrate the effectiveness of the proposed strategy to find optimal size and location of ESS. The optimal candidates and transfer capacity for the tie-lines expansion planning are also determined. The results are found using different confidence levels to assess the optimality when the confidence level changes. The primary generation adequacy indices are evaluated to highlight the effectiveness of the proposed methodology. The optimally sized batteries allocated in the optimally selected locations around the system enhance the system’s performance economically and reliably.
Fahad Saleh Alismail. Chance Constraints Optimal Planning Strategy of Energy Storage Systems and Tie-Lines under Wind Power Uncertainties to Improve the Reliability. Arabian Journal for Science and Engineering 2021, 1 -10.
AMA StyleFahad Saleh Alismail. Chance Constraints Optimal Planning Strategy of Energy Storage Systems and Tie-Lines under Wind Power Uncertainties to Improve the Reliability. Arabian Journal for Science and Engineering. 2021; ():1-10.
Chicago/Turabian StyleFahad Saleh Alismail. 2021. "Chance Constraints Optimal Planning Strategy of Energy Storage Systems and Tie-Lines under Wind Power Uncertainties to Improve the Reliability." Arabian Journal for Science and Engineering , no. : 1-10.
Even though the contribution of the aviation sector to the global economy is very notable, it also has an adverse impact on climate change. Improvements have been made in different areas (i.e., technology, sustainable aviation fuel, and design) to mitigate these adverse effects. However, the rate of improvement is small compared to the increase in the demand for air transportation. Hence, greenhouse gas emissions in the aviation sector are steadily increasing and this trend is expected to continue unless adequately addressed. In this context, this study examined the following: (i) the factors that affect the growth of aviation, (ii) trends in greenhouse gas emissions in the sector, (iii) trends in energy demand, (iv) mitigation pathways of emissions, (v) mitigation challenges for the International Civil Aviation Organization, (vi) achievements in mitigating emissions, (vii) barriers against mitigating emissions, and (viii) approaches of overcoming barriers against emissions mitigation. This study finds that continued research and development efforts targeting aircraft fuel burn efficiency are crucial in reducing greenhouse gas emissions. Although biofuels are promising for the reduction of aviation emissions, techniques to reduce NOx emissions could enhance large-scale deployment. Pragmatic market-based mechanisms, such as the Emissions Trading Scheme (ETS) and/or carbon tax must be enforced on a global scale to capitalize on a collective stakeholder effort to curb CO2 emissions. The findings of this study will help in understanding the emissions and energy consumption scenarios, which will provide a comprehensive package of mitigation pathways to overcome future emissions reduction challenges in the aviation sector.
Arif Hasan; Abdullah Mamun; Syed Rahman; Karim Malik; Al Amran; Abu Khondaker; Omer Reshi; Surya Tiwari; Fahad Alismail. Climate Change Mitigation Pathways for the Aviation Sector. Sustainability 2021, 13, 3656 .
AMA StyleArif Hasan, Abdullah Mamun, Syed Rahman, Karim Malik, Al Amran, Abu Khondaker, Omer Reshi, Surya Tiwari, Fahad Alismail. Climate Change Mitigation Pathways for the Aviation Sector. Sustainability. 2021; 13 (7):3656.
Chicago/Turabian StyleArif Hasan; Abdullah Mamun; Syed Rahman; Karim Malik; Al Amran; Abu Khondaker; Omer Reshi; Surya Tiwari; Fahad Alismail. 2021. "Climate Change Mitigation Pathways for the Aviation Sector." Sustainability 13, no. 7: 3656.
Motorcycles and motorcyclists have a variety of attributes that have been found to be a potential contributor to the high liability of vulnerable road users (VRUs). Vulnerable Road Users (VRUs) that include pedestrians, bicyclists, cycle-rickshaw occupants, and motorcyclists constitute by far the highest share of road traffic accidents in developing countries. Motorized three-wheeled Rickshaws (3W-MR) is a popular public transport mode in almost all Pakistani cities and is used primarily for short trips to carry passengers and small-scale goods movement. Despite being an important mode of public transport in the developing world, little work has been done to understand the factors affecting the injury severity of three-wheeled motorized vehicles. Crash injury severity prediction is a promising research target in traffic safety. Traditional statistical models have underlying assumptions and predefined associations, which can yield misleading results if flouted. Machine learning(ML) is an emerging non-parametric method that can effectively capture the non-linear effects of both continuous and discrete variables without prior assumptions and achieve better prediction accuracy. This research analyzed injury severity of three-wheeled motorized rickshaws (3W-MR) using various machine learning-based identification algorithms, i.e., Decision jungle (DJ), Random Forest (RF), and Decision Tree (DT). Three years of crash data (from 2017 to 2019) was collected from Provincial Emergency Response Service RESCUE 1122 for Rawalpindi city, Pakistan. A total of 2,743 3W-MR crashes were reported during the study period that resulted in 258 fatalities. The predictive performance of proposed ML models was assessed using several evaluation metrics such as overall accuracy, macro-average precision, macro-average recall, and geometric means of individual class accuracies. Results revealed that DJ with an overall accuracy of 83.7 % outperformed the DT and RF-based on a stratified 10-fold cross-validation approach. Finally, Spearman correlation analysis showed that factors such as the lighting condition, crashes involving young drivers (aged 20–30 years), facilities with high-speed limits (over 60 mph), weekday, off-peak, and shiny weather conditions were more likely to worsen injury severity of 3W-MR crashes. The outcomes of this study could provide necessary and essential guidance to road safety agencies, particularly in the study area, for proactive implementation of appropriate countermeasures to curb road safety issues pertaining to three-wheeled motorized vehicles.
Muhammad Ijaz; Liu Lan; Muhammad Zahid; Arshad Jamal. A comparative study of machine learning classifiers for injury severity prediction of crashes involving three-wheeled motorized rickshaw. Accident Analysis & Prevention 2021, 154, 106094 .
AMA StyleMuhammad Ijaz, Liu Lan, Muhammad Zahid, Arshad Jamal. A comparative study of machine learning classifiers for injury severity prediction of crashes involving three-wheeled motorized rickshaw. Accident Analysis & Prevention. 2021; 154 ():106094.
Chicago/Turabian StyleMuhammad Ijaz; Liu Lan; Muhammad Zahid; Arshad Jamal. 2021. "A comparative study of machine learning classifiers for injury severity prediction of crashes involving three-wheeled motorized rickshaw." Accident Analysis & Prevention 154, no. : 106094.
In recent years, due to the wide utilization of direct current (DC) power sources, such as solar photovoltaic (PV), fuel cells, different DC loads, high-level integration of different energy storage systems such as batteries, supercapacitors, DC microgrids have been gaining more importance. Furthermore, unlike conventional AC systems, DC microgrids do not have issues such as synchronization, harmonics, reactive power control, and frequency control. However, the incorporation of different distributed generators, such as PV, wind, fuel cell, loads, and energy storage devices in the common DC bus complicates the control of DC bus voltage as well as the power-sharing. In order to ensure the secure and safe operation of DC microgrids, different control techniques, such as centralized, decentralized, distributed, multilevel, and hierarchical control, are presented. The optimal planning of DC microgrids has an impact on operation and control algorithms; thus, coordination among them is required. A detailed review of the planning, operation, and control of DC microgrids is missing in the existing literature. Thus, this article documents developments in the planning, operation, and control of DC microgrids covered in research in the past 15 years. DC microgrid planning, operation, and control challenges and opportunities are discussed. Different planning, control, and operation methods are well documented with their advantages and disadvantages to provide an excellent foundation for industry personnel and researchers. Power-sharing and energy management operation, control, and planning issues are summarized for both grid-connected and islanded DC microgrids. Also, key research areas in DC microgrid planning, operation, and control are identified to adopt cutting-edge technologies. This review explicitly helps readers understand existing developments on DC microgrid planning, operation, and control as well as identify the need for additional research in order to further contribute to the topic.
Fahad Saleh Al-Ismail. DC Microgrid Planning, Operation, and Control: A Comprehensive Review. IEEE Access 2021, 9, 36154 -36172.
AMA StyleFahad Saleh Al-Ismail. DC Microgrid Planning, Operation, and Control: A Comprehensive Review. IEEE Access. 2021; 9 ():36154-36172.
Chicago/Turabian StyleFahad Saleh Al-Ismail. 2021. "DC Microgrid Planning, Operation, and Control: A Comprehensive Review." IEEE Access 9, no. : 36154-36172.
Since renewable power is intermittent and uncertain, modern grid systems need to be more elegant to provide a reliable, affordable, and sustainable power supply. This paper introduces a robust optimal planning strategy to find the location and the size of an energy storage system (ESS) and feeders. It aims to accommodate the wind power energy integration to serve the future demand growth under uncertainties. The methodology was tested in the IEEE RTS-96 system and the simulation results demonstrate the effectiveness of the proposed optimal sizing strategy. The findings validate the improvements in the power system reliability and flexibility.
Fahad Alismail; Mohamed Abdulgalil; Muhammad Khalid. Optimal Coordinated Planning of Energy Storage and Tie-Lines to Boost Flexibility with High Wind Power Integration. Sustainability 2021, 13, 2526 .
AMA StyleFahad Alismail, Mohamed Abdulgalil, Muhammad Khalid. Optimal Coordinated Planning of Energy Storage and Tie-Lines to Boost Flexibility with High Wind Power Integration. Sustainability. 2021; 13 (5):2526.
Chicago/Turabian StyleFahad Alismail; Mohamed Abdulgalil; Muhammad Khalid. 2021. "Optimal Coordinated Planning of Energy Storage and Tie-Lines to Boost Flexibility with High Wind Power Integration." Sustainability 13, no. 5: 2526.
Statistical modeling of historical crash data can provide essential insights to safety managers for proactive highway safety management. While numerous studies have contributed to the advancement from the statistical methodological front, minimal research efforts have been dedicated to real-time monitoring of highway safety situations. This study advocates the use of statistical monitoring methods for real-time highway safety surveillance using three years of crash data for rural highways in Saudi Arabia. First, three well-known count data models (Poisson, negative binomial, and Conway–Maxwell–Poisson) are applied to identify the best fit model for the number of crashes. Conway–Maxwell–Poisson was identified as the best fit model, which was used to find the significant explanatory variables for the number of crashes. The results revealed that the road type and road surface conditions significantly contribute to the number of crashes. From the perspective of real-time highway safety monitoring, generalized linear model (GLM)-based exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts are proposed using the randomized quantile residuals and deviance residuals of Conway–Maxwell (COM)–Poisson regression. A detailed simulation-based study is designed for predictive performance evaluation of the proposed control charts with existing counterparts (i.e., Shewhart charts) in terms of the run-length properties. The study results showed that the EWMA type control charts have better detection ability compared with the CUSUM type and Shewhart control charts under small and/or moderate shift sizes. Finally, the proposed monitoring methods are successfully implemented on actual traffic crash data to highlight the efficacy of the proposed methods. The outcome of this study could provide the analysts with insights to plan sound policy recommendations for achieving desired safety goals.
Arshad Jamal; Tahir Mahmood; Muhamad Riaz; Hassan Al-Ahmadi. GLM-Based Flexible Monitoring Methods: An Application to Real-Time Highway Safety Surveillance. Symmetry 2021, 13, 362 .
AMA StyleArshad Jamal, Tahir Mahmood, Muhamad Riaz, Hassan Al-Ahmadi. GLM-Based Flexible Monitoring Methods: An Application to Real-Time Highway Safety Surveillance. Symmetry. 2021; 13 (2):362.
Chicago/Turabian StyleArshad Jamal; Tahir Mahmood; Muhamad Riaz; Hassan Al-Ahmadi. 2021. "GLM-Based Flexible Monitoring Methods: An Application to Real-Time Highway Safety Surveillance." Symmetry 13, no. 2: 362.
The high-level penetration of renewable energy sources (RESs) is the main reason for shifting the conventional centralized power system control paradigm into distributed power system control. This massive integration of RESs faces two main problems: complex controller structure and reduced inertia. Since the system frequency stability is directly linked to the system’s total inertia, the renewable integrated system frequency control is badly affected. Thus, a fractional order controller (FOC)-based superconducting magnetic energy storage (SMES) is proposed in this work. The detailed modeling of SMES, FOC, wind, and solar systems, along with the power network, is introduced to facilitate analysis. The FOC-based SMES virtually augments the inertia to stabilize the system frequency in generation and load mismatches. Since the tuning of FOC and SMES controller parameters is challenging due to nonlinearities, the whale optimization algorithm (WOA) is used to optimize the parameters. The optimized FOC-based SMES is tested under fluctuating wind and solar powers. The extensive simulations are carried out using MATLAB Simulink environment considering different scenarios, such as light and high load profile variations, multiple load profile variations, and reduced system inertia. It is observed that the proposed FOC-based SMES improves several performance indices, such as settling time, overshoot, undershoot compared to the conventional technique.
Alam; Majed Alotaibi; Alam; Alamgir Hossain; Shafiullah; Fahad Al-Ismail; Mamun Ur Rashid; Mohammad Abido. High-Level Renewable Energy Integrated System Frequency Control with SMES-Based Optimized Fractional Order Controller. Electronics 2021, 10, 511 .
AMA StyleAlam, Majed Alotaibi, Alam, Alamgir Hossain, Shafiullah, Fahad Al-Ismail, Mamun Ur Rashid, Mohammad Abido. High-Level Renewable Energy Integrated System Frequency Control with SMES-Based Optimized Fractional Order Controller. Electronics. 2021; 10 (4):511.
Chicago/Turabian StyleAlam; Majed Alotaibi; Alam; Alamgir Hossain; Shafiullah; Fahad Al-Ismail; Mamun Ur Rashid; Mohammad Abido. 2021. "High-Level Renewable Energy Integrated System Frequency Control with SMES-Based Optimized Fractional Order Controller." Electronics 10, no. 4: 511.
Proactive management at mass gatherings is vital to ensure safe crowd evacuation during emergencies. The increasing number of crowd incidents and casualties during the Hajj season is one of the major concerns for authorities in Saudi Arabia. This study aims to explore and analyze crowd dynamics visiting the Prophet's (PBUH) tomb at the visiting (Ziara) corridor in the Holy Mosque of Madinah under continuous flow conditions. MassMotion was used to optimize the crowd flow rate with density restricted to a safe threshold value for efficient crowd management. A robust regression model has been developed to guide the authorities for the safe and efficient operation of the visiting corridor. The study results showed that the crowd flow beyond 9200 persons/h and waiting time in excess of 42 s in front of Moajha might lead to breakdown condition. The output of this study can be utilized by decision-makers and concerned authorities to take appropriate and timely remedial actions to ensure safe, smooth, and efficient crowd management.
Hassan M. Al-Ahmadi; Imran Reza; Arshad Jamal; Wael S. Alhalabi; Khaled J. Assi. Preparedness for Mass Gatherings: A Simulation-Based Framework for Flow Control and Management Using Crowd Monitoring Data. Arabian Journal for Science and Engineering 2021, 46, 4985 -4997.
AMA StyleHassan M. Al-Ahmadi, Imran Reza, Arshad Jamal, Wael S. Alhalabi, Khaled J. Assi. Preparedness for Mass Gatherings: A Simulation-Based Framework for Flow Control and Management Using Crowd Monitoring Data. Arabian Journal for Science and Engineering. 2021; 46 (5):4985-4997.
Chicago/Turabian StyleHassan M. Al-Ahmadi; Imran Reza; Arshad Jamal; Wael S. Alhalabi; Khaled J. Assi. 2021. "Preparedness for Mass Gatherings: A Simulation-Based Framework for Flow Control and Management Using Crowd Monitoring Data." Arabian Journal for Science and Engineering 46, no. 5: 4985-4997.
Presents a discussion to the above named paper.
Fahad S. Al-Ismail. Discussion on “A New Formulation of Distribution Network Reconfiguration for Reducing the Voltage Volatility Induced by Distributed Generation”. IEEE Transactions on Power Systems 2020, 35, 4974 -4974.
AMA StyleFahad S. Al-Ismail. Discussion on “A New Formulation of Distribution Network Reconfiguration for Reducing the Voltage Volatility Induced by Distributed Generation”. IEEE Transactions on Power Systems. 2020; 35 (6):4974-4974.
Chicago/Turabian StyleFahad S. Al-Ismail. 2020. "Discussion on “A New Formulation of Distribution Network Reconfiguration for Reducing the Voltage Volatility Induced by Distributed Generation”." IEEE Transactions on Power Systems 35, no. 6: 4974-4974.
Installing capacitors to correct the power factor at particular locations is one way to enhance power system reliability. This paper offers a new formulation to address the issue of optimal placing capacitors. The proposed formulation considers reliability impact, in addition to the transient switching events. This is reflected in the cost minimization objective function, where the reliability calculations are considered to gauge the impact when capacitors are installed in the power system. The formulated problem is solved using genetic algorithm (GA), to minimize costs of capacitor installation, energy loss and failure impact. The new formulation has been examined on a test network for evaluating how effective the proposed approach is. The solution also considers the impact of uncertainties as well as future growth in the system, to ensure that it is optimal. The results evidence that the proposed approach is robust and effective in enhancing system reliability in the face of uncertainties and for future growth.
A. A. Al-Muhanna; M. A. Abido; F. S. Al-Ismail. Assessing Impact of Optimally Placed Power Factor Correction Capacitors Reckoning Transient Switching Events. Arabian Journal for Science and Engineering 2020, 46, 1269 -1277.
AMA StyleA. A. Al-Muhanna, M. A. Abido, F. S. Al-Ismail. Assessing Impact of Optimally Placed Power Factor Correction Capacitors Reckoning Transient Switching Events. Arabian Journal for Science and Engineering. 2020; 46 (2):1269-1277.
Chicago/Turabian StyleA. A. Al-Muhanna; M. A. Abido; F. S. Al-Ismail. 2020. "Assessing Impact of Optimally Placed Power Factor Correction Capacitors Reckoning Transient Switching Events." Arabian Journal for Science and Engineering 46, no. 2: 1269-1277.
A better understanding of circumstances contributing to the severity outcome of traffic crashes is an important goal of road safety studies. An in-depth crash injury severity analysis is vital for the proactive implementation of appropriate mitigation strategies. This study proposes an improved feed-forward neural network (FFNN) model for predicting injury severity associated with individual crashes using three years (2017–2019) of crash data collected along 15 rural highways in the Kingdom of Saudi Arabia (KSA). A total of 12,566 crashes were recorded during the study period with a binary injury severity outcome (fatal or non-fatal injury) for the variable to be predicted. FFNN architecture with back-propagation (BP) as a training algorithm, logistic as activation function, and six number of hidden neurons in the hidden layer yielded the best model performance. Results of model prediction for the test data were analyzed using different evaluation metrics such as overall accuracy, sensitivity, and specificity. Prediction results showed the adequacy and robust performance of the proposed method. A detailed sensitivity analysis of the optimized NN was also performed to show the impact and relative influence of different predictor variables on resulting crash injury severity. The sensitivity analysis results indicated that factors such as traffic volume, average travel speeds, weather conditions, on-site damage conditions, road and vehicle type, and involvement of pedestrians are the most sensitive variables. The methods applied in this study could be used in big data analysis of crash data, which can serve as a rapid-useful tool for policymakers to improve highway safety.
Arshad Jamal; Waleed Umer. Exploring the Injury Severity Risk Factors in Fatal Crashes with Neural Network. International Journal of Environmental Research and Public Health 2020, 17, 7466 .
AMA StyleArshad Jamal, Waleed Umer. Exploring the Injury Severity Risk Factors in Fatal Crashes with Neural Network. International Journal of Environmental Research and Public Health. 2020; 17 (20):7466.
Chicago/Turabian StyleArshad Jamal; Waleed Umer. 2020. "Exploring the Injury Severity Risk Factors in Fatal Crashes with Neural Network." International Journal of Environmental Research and Public Health 17, no. 20: 7466.