Transportation Engineering Research Articles

LIII. International Scientific Conference KoKa 2022 September 7 – 9, 2022, Kočovce, Slovak Republic

Abstract Faculties of Mechanical Engineering, especially their Departments of Internal Combustion Engines, began conferences with a later designation KOKA (or KoKa) in the year 1969. These were initially focused on the research of the combustion engines. This was later accompanied also by research of the vehicle powertrains and drive units in general. Latest of these conferences was organized by the Institute of Transport technology and Engineering Design, SjF, STU in the year 2022 in the mansion house Kočovce.

Editorial: Special Issue on Smart and Green Infrastructures with Optimum Life Cycle Solutions

Editorial: Special Issue on Smart and Green Infrastructures with Optimum Life Cycle Solutions

Improving Online Adaptive Radiotherapy Quality Assurance with Streamlined Clinical Workflow through In-House Development

<h3>Purpose/Objective(s)</h3> Online adaptive radiotherapy has been clinically feasible through decades of research and development and is now available in the clinical routine with dedicated platforms using CBCT-LINAC or MR-LINAC. The quality assurance (QA) of online plans has become a bottleneck in the clinical workflow as it often requires manual data export/import through third party software, lengthy wait for the secondary dose calculation, and tedious work on report generation and checking, etc. The QA bottleneck not only impedes clinical workflow but also risks plan and treatment quality due to the time pressure with the patient waiting on the treatment table. We have developed and implemented in-house solutions to address such a bottleneck. <h3>Materials/Methods</h3> We developed dedicated in-house infrastructure to facilitate online adaptive plan QA and clinical workflow: 1) RT-PACK with SQLite database, which receives and organizes DICOM-RT data from any DICOM sender (e.g., clinical TPS); 2) a general purpose dose calculation server powered by the in-house GPU-based Monte Carlo particle transport engine with electromagnetic field modelling; 3) a report generator that automatically generates reports for secondary dose and plan quality check; 4) a web-portal that allows clinicians to review and sign the report anywhere with a network and VPN connection, even from a mobile phone. The reports and related documents will be automatically sent to the Record & Verify system after obtaining both physician and physicist signatures. An auto-commissioner was also developed to facilitate beam modeling based on water-tank measurements, which serves the purpose of fully independent verification. The dose calculation was performed on the whole patient volume with grid resolution of 2 mm x 2 mm x 2 mm. The 3D dose volume, treatment fields, point dose, Gamma Index with global 3%, 2mm criteria, three orthogonal dose profiles, dose volume histograms, and dosimetric constraints are metrics to compare the plan retrieved from TPS to the secondary dose verification and reported for clinicians' review. The whole in-house infrastructure went through extensive unit tests, dosimetric accuracy verifications, and alpha and beta tests before adopted for clinical use. <h3>Results</h3> The secondary dose and plan check infrastructure went live for CBCT-LINAC and MR-LINAC in our clinic and has since performed secondary check for every plan generated (846 plans and 622 plans, respectively, in less than 6 months.) The average processing time, from DICOM receiving to report generation, was 62 seconds for CBCT-LINAC and 130 seconds for MR-LINAC, which was 3-5 minutes shorter compared to using commercial software. More than 95% of CBCT-LINAC (MR-LINAC) plans had Gamma passing rates >99% (>95%). <h3>Conclusion</h3> The in-house developed software, through strict verification and validation, has been integrated into the clinical system. It has greatly improved online adaptive quality assurance with efficient and streamlined clinical workflow.

ADAPTING A DIGITAL TWIN TO ENABLE REAL-TIME WATER SENSITIVE URBAN DESIGN DECISION-MAKING

Abstract. Landscape architects and urban designers are often tasked with decision-making about implementation of flood moderating measures in urban renewal projects. These decisions require consideration of complex, interdependent existing and proposed infrastructure, and must be informed by data and modelling from multiple disciplines such as hydrologists, transport engineers and urban planners. Here we describe the challenges of integrating these data and modelling from both GIS and BIM sources, into a framework that could support flood moderation decision-making, embedded within a spatially enabled Digital Twin. Our findings outline some of the considerable adjustments to future data collection methods that will be required to enable such a decision-support framework. Furthermore, we outline the requirements of the framework for employability in stakeholders and community decision-making forums. We test this framework on a large-scale urban renewal precinct in Melbourne Australia, with well recognised current and future flooding issues.

Hardox 450 Weld in Microstructural and Mechanical Approaches after Welding at Micro-Jet Cooling.

The demand for high-strength steel welds, as observed in civil and transport engineering, is related to a mass reduction in vehicles. Container-type trucks are examples of this kind of transport means because their boxes are able to be produced using Hardox grade steels. Therefore, this study reflects on the properties of welds in the MAG welding of Hardox 450, obtained through an innovative micro-jet cooling process with helium. This joining technology aims to reduce the formation of defects and to obtain a joint with very good assumed mechanical properties. Structural components of grade steel require welds with acceptable mechanical parameters with respect to operational loading conditions. That is, this study focuses on selecting welding parameters for the Hardox 450 steel and determining the weld quality with respect to microstructural observations and mechanical tests, such as the Charpy, tensile and fatigue tests. Weld fracturing under increasing monotonic force was examined and was strongly related to both stress components, i.e., axial and shear. The joint response under fatigue was expressed through differences in the fracture zones, i.e., at a stress value lower than the proportional limit, and weld degradation occurred in the shear and axial stress components. The data indicate that the hourglass specimen, with the weld in the centre zone of the measurement section, can be directly used to determine a weld response under cyclic loading. The impact test results showed attractive behaviour in the tested joint, as represented by 47 J at −20 °C. The recommended MAG welding parameters for Hardox 450 steel are low-oxygen when using an Ar + 18% CO2 shielding mixture. The collected results can be directly used as a guide to weld thin-walled structures (6 mm) made of Hardox grade steel, while the data from mechanical tests can support the modelling, designing and manufacturing of components made from this kind of steel grade.

Vehicle Trip Reduction Impacts of Transit-Oriented Housing

A survey of 17 transit-oriented developments (TOD) in five U.S. metropolitan areas showed that vehicle trips per dwelling unit were substantially below what the Institute of Transportation Engineer’s Trip Generation manual estimates. Over a typical weekday period, the surveyed TOD housing projects averaged 44 percent fewer vehicle trips than that estimated by the manual (3.754 versus 6.715). Vehicle trip rates of transit-oriented housing projects were particularly low in metropolitan Washington, D.C. and Portland, Oregon, both known for successful TOD planning at the regional and corridor levels. Trip rates also generally fell as neighborhood densities increased. Local officials should account for the lower automobile use of those residing in TOD housing through such measures as traffic impact-fee adjustments and reduced off-street parking requirements.

Predicting Pavement Condition Index Using Machine Learning Algorithms and Conventional Techniques

Government agencies and transportation engineers use pavement management systems (PMS) to evaluate pavement performance and keep pavement above the minimum acceptable performance standards. The Pavement Condition Index (PCI) and the international roughness index (IRI) are among the most commonly used indices to evaluate pavement conditions. Due to IRI data collection being more accessible and less expensive than collecting pavement distress data, this study aims to develop PCI models that can successfully estimate the PCI values based on IRI for flexible pavement using two Machine Learning techniques (ML), namely: Random Forest (RF), and Support Vector Machine (SVM), and three conventional techniques, namely: linear, quadratic, and cubic regression. The study was carried out with the database collected from the Long-Term Pavement Performance (LTPP) program. The results of the dataset reveal that both ML models (RF and SVM) have strong prediction ability with high values of coefficient of determination (R^2 = 99.7 and 96.8) %, and low values of Root Mean Squared Error (RMSE = 1.095 and 3.569) % and Mean Absolute Error (MAE = 0.474 and 2.244). In conclusion, the goodness of fit of the proposed ML models was compared with conventional techniques models previously developed. The results showed that the ML models yielded higher prediction accuracy than conventional techniques.

Generating robust dispatching solutions

Not least because of the increasing demand for transport and limited possibilities to expand railway infrastructures, efficient dispatching approaches gain in importance. The Institute of Railway and Transportation Engineering at the University of Stuttgart developed a proactive dispatching algorithm, which automatically generates robust dispatching solutions while taking random disturbances in dynamic circumstances into account.

Preface

The conference on Sustainable Energy, Environment, and Green Technologies (ICSEEGT 2022) is the second international conference organized at Poornima College of Engineering, Jaipur, Rajasthan, India. This event was organized in a hybrid mode. This conference aims to bring researchers from academia, government agencies, research laboratories, and the corporate sector to present their research on sustainable and renewable energy, the environment, transportation engineering and green technologies. Since green growth is pursuing economic development in an environmentally sustainable manner, therefore green growth must play a vital role in the development goal of improving living standards, accessing modern energy services, and using energy more efficiently. For this aim, the conference ICSEEGT 2022 provided an excellent platform to promote research in the subject area and exchange new ideas in these fields among academicians, engineers, scientists, and practitioners across the world.The conference began with its inaugural session (in hybrid mode), seeking the blessings of Goddess Saraswati. The session witnessed addresses of dignified persons, Professor S.A Sherif, Department of Mechanical and Aerospace Engineering, University of Florida, USA, Professor L.M. Das, Former Professor, Centre for Energy Studies, Indian Institute of Technology, Delhi, India and Dr. L. N. Thakural, Senior Scientist, Surface Water Division, National Institute of Hydrology, Roorkee, India.The inaugural session was followed by a keynote session of Professor P. Muthukumar, Professor, Indian Institute of Technology, Guwahati, India, on the Energy Efficient and Environment Friendly Porous Radiant Burners for Cooking and Industrial Applications. Later, four parallel technical sessions were organized on the first day, where authors and participants participated and presented their papers. Overall, 186 research papers were received for ICSEEGT 2022 from different organizations worldwide, out of which our expert team of reviewers accepted 102 papers. The research papers in this conference were invited considering these three tracks: sustainable/renewable energy, environment and transportation, green technologies, and urban development. The presenters and attendees participated with full enthusiasm in all the technical sessions. Out of 83 registered papers, 43 papers were presented in the technical sessions on the first day. The first Technical Session in offline mode was chaired by Dr. Narayan Lal Jain and Dr. Pran Nath Dadhich, and moderated by Mr. Rahul Sharma of Poornima College of Engineering, Jaipur, India. The second Technical Session was chaired by Dr Salifu Tahiru Azeko, Tamale Technical University, Tamale, Ghana: Mr. Sanjay Kumawat, Poornima College of Engineering, was the moderator for this session. Dr. Tanuj Chopra from Thapar Institute of Engineering and Technology, Patiala, India chaired the third Technical Session. The second and third session moderator were Mr. Divya Vishnoi and Mr. Sanjay Kumawat, Poornima College of Engineering respectively. Dr. Puneet Kumar Jain, National Institute of Technology, Raurkela, and Dr. Ram Niwash Mahia, National Institute of Technology, Hamirpur, India chaired the fourth Technical Session and moderated Dr. Monika Vardia from Poornima College of Engineering.The day ended with a keynote session on Recent Advances Materials on Energy Storage Technology and Sustainability by Dr. M V Reddy, Senior Professional Researcher, Nouveau Monde Graphite (New graphite world) (NMG), Quebec, Montreal, Canada.List of ORGANIZING COMMITTEES are available in this Pdf.

Analysis of Factors Influencing Wave Overtopping Discharge from Breakwater Based on an MIV-BP Estimation Model

Aiming at the problem of calculating the overtopping of single-slope breakwaters, a mean impact value-backpropagation (MIV-BP) estimation model for predicting overtopping was established. Experimental data from the Tianjin Research Institute of Water Transport Engineering (TIWTE) were utilized to further enrich the dataset of the CLASH project for single-slope wave overtopping discharge. This paper established a comprehensive prediction model based on an ensemble learning average method combination strategy. There are 10 input parameters in the model, including the offshore effective wave height, average wave period, offshore water depth, toe submergence, toe width, slope tangent, armor rock surface roughness factor, crest height with respect to the static water level, wall height with respect to the static water level, and crest width; the output parameter is the mean overtopping discharge. Subsequently, a comparative analysis was conducted between this estimation model, the Chinese standard formula calculation model, and the European Van der Meer formula calculation model. Compared with the two formulas mentioned above, this estimation model’s coefficient of correlation increased by 0.23 and 0.26, respectively. Finally, a weight evaluation analysis of the 10 main factors affecting overtopping was carried out based on a MIV-BP neural network model. In the analysis, a positive correlation was found for factors, such as the wave height, average wave period, and water depth at the structure toe; a negative correlation was found for factors, such as the slope, crest height with respect to the static water level, wall height with respect to the static water level, and crest width. Overall, the results provide a significant basis and reference for optimizing the design of the wave overtopping control.

ANALYSIS OF ALTERNATIVE FUEL PROCESSING TECHNOLOGIES

The article presents the results of a comparative analysis and experimental testing of the efficiency of technological processes for the processing of some types of alternative energy sources into fuel for transport engines.&#x0D; The accumulated research experience in the development of on-board conversion systems (reactors) of traditional motor fuels shows that the level of their technical and technological complexity is incomparable with the ecological and economic effect of their use in an RTS power plant. The high temperature level of the processing of these fuels necessitates the need for additional energy expenditure for the organization of the conversion process (for example, burning part of the fuel to support the necessary thermal regime of operation in thermochemical reactors), and the presence of sulfur compounds in motor fuel excludes the possibility of using highly efficient catalysts. In addition, the large relative content of inert (non-combustible) components in the composition of the target conversion products create additional difficulties when they are burned in the engine. In general, the choice of an acceptable alternative energy carrier as a raw product for the production of motor fuel is a compromise that takes into account its energy value, temperature conditions of conversion, the spectrum of gases formed during conversion, cost, availability of raw materials, the possibility of adaptation to the conditions of the RTS, etc. From the set of factors considered above, it can be concluded that today methanol is one of the most energetically beneficial sources of cheap and efficient hydrogen-containing fuel for RTS engines. It should be noted that in the future, in the world of technology development and the corresponding raw material bases, it may be economically justified to use other compounds, which, according to their characteristics, will be able to meet the energetically favorable conditions in the technological structure of the on-board conversion implementation. This will allow creating a stable fuel and energy base , which practically does not depend on the imported hydrocarbon fuel.

Activity-based integrated modelling for assessing COVID-19 impacts on transport operations and emissions

ABSTRACT This study combines an integrated transport, land-use, and energy (iTLE) modeling system with traffic microsimulation model and emission simulator for a holistic analysis of COVID-19 pandemic related changes in traffic flows and emissions. An activity-based travel demand model within iTLE informs pandemic traffic operation scenarios for traffic microsimulation modeling. Link-based simulation outputs inform a finer-grained emission estimation process within a MOtor Vehicle Emission Simulator. Results suggest that the overall network performance improves during lockdown as average delays and queue time decrease by 42.04% and 5.9% respectively compared to pre-COVID condition. Emission results reveal that GHG emissions significantly decrease (64%) in lockdown while it starts increasing gradually in post-pandemic period. Link-based emission analysis indicates that major arterial streets achieve a significant reduction in air pollutant emission. The findings of this study will help transportation planners, engineers, and policymakers to devise effective policies for the improvement of transport operations and emissions.

Glucose transport engineering allows mimicking fed-batch performance in batch mode and selection of superior producer strains

BackgroundFed-batch mode is the standard culture technology for industrial bioprocesses. Nevertheless, most of the early-stage cell and process development is carried out in batch cultures, which can bias the initial selection of expression systems. Cell engineering can provide an alternative to fed-batch cultures for high-throughput screening and host selection. We have previously reported a library of Escherichia coli strains with single and multiple deletions of genes involved in glucose transport. Compared to their wild type (W3110), the mutant strains displayed lower glucose uptake, growth and aerobic acetate production rates. Therefore, when cultured in batch mode, such mutants may perform similar to W3110 cultured in fed-batch mode. To test that hypothesis, we evaluated the constitutive expression of the green fluorescence protein (GFP) in batch cultures in microbioreactors using a semi defined medium supplemented with 10 or 20 g/L glucose + 0.4 g yeast extract/g glucose.ResultsThe mutant strains cultured in batch mode displayed a fast-growth phase (growth rate between 0.40 and 0.60 h−1) followed by a slow-growth phase (growth rate between 0.05 and 0.15 h−1), similar to typical fed-batch cultures. The phase of slow growth is most probably caused by depletion of key amino acids. Three mutants attained the highest GFP fluorescence. Particularly, a mutant named WHIC (ΔptsHIcrr, ΔmglABC), reached a GFP fluorescence up to 14-fold greater than that of W3110. Strain WHIC was cultured in 2 L bioreactors in batch mode with 100 g/L glucose + 50 g/L yeast extract. These cultures were compared with exponentially fed-batch cultures of W3110 maintaining the same slow-growth of WHIC (0.05 h−1) and using the same total amount of glucose and yeast extract than in WHIC cultures. The WHIC strain produced approx. 450 mg/L GFP, while W3110 only 220 mg/L.ConclusionThe combination of cell engineering and high throughput screening allowed the selection of a particular mutant that mimics fed-batch behavior in batch cultures. Moreover, the amount of GFP produced by the strain WHIC was substantially higher than that of W3110 under both, batch and fed-batch schemes. Therefore, our results represent a valuable technology for accelerated bioprocess development.

Modernization of products in transport engineering during the transition to the sixth technological order

The methods of modernization of transport engineering products during the transition to the sixth technological order (STO) are considered in order to increase the effectiveness of modernization. The essence and content of the elements of the sixth technological order, neurotechnologies in post-industrial engineering, are analyzed. The methods of logical analysis and synthesis, as well as the multiplication of technologies in transport engineering, the formation of a criteria basis for assessing the effectiveness of the development of the industry within the framework of the STO are considered. Keywords: mechanical engineering, transport, the sixth technological order, modernization, methodology, products, criterion, production, effectiveness, structure. glu-valery@yandex.ru

Crash prediction for freeway work zones in real time: A comparison between Convolutional Neural Network and Binary Logistic Regression model

Safety of drivers in freeway work zones has been a problem. Real-time crash prediction helps prevent crashes before they happen. This paper looks at real-time crash prediction in freeway work zones by using machine learning approaches. Both the Convolutional Neural Network and the Binary Logistic Regression model are introduced. For training and testing the models, crash data and traffic data from several freeways in D7 zone, Los Angeles, California, were used. Crash data were collected from California Highway Patrol Incident System, and traffic data were obtained from the Caltrans Performance Measurement System. Data processing and matching were conducted. Both the two models were trained and tested. Results show that the Convolutional Neural Network performed slightly better over the Binary Logistic Regression model in predicting crashes with a global accuracy of 79.50%. Despite this, the main merit of the Binary Logistic Regression model is that it is able estimate the impact of affecting variables on the probability of crashes and can help identify the factors related to risks in work zones. Machine learning approaches applied in this study perform well in crash prediction. In general, machine learning techniques and reliable real-time crash prediction applications can be promising in helping drivers and transportation engineers make timely responses to potential crashes on freeways.

Pseudo-equivalent deterministic excitation method application for experimental reproduction of a structural response to a turbulent boundary layer excitation.

In the transportation engineering field, the turbulent boundary layer over a structure is one of the most relevant sources of structural vibration and emitted noise. Wind tunnels are still one of the best options for vibroacoustic experimental analyses for this specific problem. However, it is also true that this experimental method is not always affordable, due to several limitations-settings hard to control, time and money consumption, discrepancies among laboratories-that wind tunnel facilities present. It has already developed different methodologies to address this necessity, most of them based on the use of loudspeakers or shakers. In this work, an existing numerical method, called the pseudo-equivalent deterministic excitation method (PEDEM), is further developed for the experimental purpose of reproducing the experimental structural response of a panel subjected to a turbulent boundary layer (TBL) excitation, by using an equivalent rain-on-the-roof excitation instead; different formulations are used for the application of this approximated TBL excitation. The experimental application of PEDEM, here called X-PEDEM, is validated by comparison with experimental results of two different panels analysed in two different wind tunnel facilities.

Study on city digital twin technologies for sustainable smart city design: A review and bibliometric analysis of geographic information system and building information modeling integration

• Analyzes the future research trend of GIS and BIM integration through literature review. • GIS and BIM integration has been the basic technology to realize smart cities. • Future research should focus on smart city and urban rail transportation. Geographic information system (GIS) data provide geospatial data on cities and spatial analysis functions that are essential for urban design. Building information modeling (BIM) includes a digital entity of construction, a passive presentation of micro-digital information on real entities, and an active application of models in the entire life cycle realization of the architecture, engineering, and construction industries. A combination of these technologies could provide a core technology for the urban digital twin to support sustainable smart city design. Through an insightful literature review, this paper summarizes the different disciplinary classifications of GIS and BIM functional integration, distills the value of data, and discusses the ontology-based data integration approach that GIS and BIM should take in the future to conduct research on integration applications in smart cities. To verify this view, keyword analysis, co-country analysis, and co-citation and coupling analyses are conducted using CiteSpace. GIS and BIM integration has attracted much attention. However, a professional disconnect and fragmented composition pose challenges in the field of GIS and BIM integration. Future research should focus on smart city planning, updating, management; ontology-based GIS and BIM data integration platform; and operation; and the collaborative management of urban rail transportation engineering.

Glucose transport engineering allows mimicking fed‐batch performance in batch mode and selection of superior producer strains

Glucose transport engineering allows mimicking fed‐batch performance in batch mode and selection of superior producer strains

Анализ вредных сбросов в гидросферу от дизельного подвесного лодочного мотора Yanmar D27

The article considers the necessity of studying the atmosphere and hydrosphere pollution due to the operation of marine transport engines and the introduction of relevant regulatory documents in the Russian Federation is substantiated. Today the problems of harmful emissions into the environment are considered haphazardly, there are few foreign authors studying the problem. Since 2016, the environmental characteristics of outboard motors in laboratory and scientific conditions have been studied at the Department of Water Transport Operation at the Astrakhan State Technical University. The results of practical measurements of harmful discharges into the hydrosphere from the Yanmar D2 outboard motor are presented. General characteristics of the Yanmar D2 engine are listed (rated power, rated speed, number of cylinders, fuel used, etc.), the general view of the outboard motor is illustrated. A detailed description of the laboratory equipment is given and the technical characteristics of control and measuring instruments (concentrator KN-3 and spectrophotometer PE-5400VI) are listed. It is pointed out that the small experimental pool of the laboratory has patents for a utility model; a schematic diagram of the pool is given. New data on discharges of film and dissolved petroleum products, phosphate ions and total phosphorus into the hydrosphere have been obtained, empirical formulas for calculating the expected level of discharges from a diesel outboard motor depending on its operation time have been developed.

Evaluation of Interaction between Bridge Infrastructure Resilience Factors against Seismic Hazard

Infrastructure systems, such as bridges, are perpetually vulnerable to natural hazards such as seismic events, flooding, and landslides. This study aims to determine the relevant parameters required to increase the seismic resilience of bridge infrastructure based on the decisions of experts and prior research. To this end, the crisp DEMATEL (decision-making and trial evaluation laboratory) and rough DEMATEL methods are employed. Rough DEMATEL is a supplement to crisp DEMATEL that incorporates rough theory to handle ambiguity. The efficacies of the rough and crisp DEMATEL methods are then compared between the two approaches. This study found the most crucial seismic-resilience variables for bridges. The outcomes of this study reveal the significant order and cause-and-effect relationships. This research can assist transportation engineers and executive agencies in enhancing the seismic resilience of roadway bridges and bridge networks.