This paper describes the study of ventilated car disc brakes stress-strain conditions and friction under the pressure using the ANSYS environment. Such influencing factors are taken into account in the course of research as angular speed value, the pressure of the pads on the disk, the nature of the load application, convection, thermal expansion, etc. Computer modelling of the stress field and the transient thermal field in the area of contact between the pads and the disk is provided by the method of sequential thermostructural communication of the intermediate states of the brake model directly in the ANSYS Coupled Field Transient environment. Besides, the ANSYS calculations were also performed based on the primitive assembly model of two steel blocks (the discrepancy was less than 3%) to determine the identity of the theoretical knowledge about the heating of bodies as a result of the work to overcome frictional forces. Finally, a high level of calculation results convergence by analytical formulas and computer modelling was established. Since this approach justified itself, its principles were taken as a basis in the calculations of ventilated disc brakes of cars, which significantly facilitates their application, knowing the area of the active part of the disc (the rest of the boundary conditions are typical and correspond to the normal operating modes of the vehicle).

The aim of the study is to estimate the air travel demand forecast of domestic passengers’ travels in Nigeria from 2002-2016. Data wesourced from Central Bank of Nigeria, National Bureau of Statistics, and Federal Airport Authority of Nigeria. The study utilized multiple regressions model using Stata-Graphic software solver to analyze the data. From the analysis, the result shows that there is significant relationship between the explanatory variable (passengers) and unexplanatory variables National Disposable Income, Population, Average Airfare, Gross Domestic Product, Exchange Rate, Total Expenditure, and Crude oil price, accounted for adjusted R of 93.624% relationship with demand for domestic air travel of passenger. The R-square statistic shows that the fitted model explains the variability in Number of passenger (NPAX) which is 96.8124%. The Hypothesis testing reveals that National Disposable Income and Air fare have strong statistically significant relationship with the demand for domestic air travel with P-value of 0.0013. Moreso, there is statistically significant relationship for National Disposable Income, Average Airfare, and Crude oil price with P-value of 0.0017 and 0.0445 respectively. Furthermore, forecast of the number of passengers and average airfare was carried out using ARIMA (1,0,0) model which made available the future predicted values for the number of passenger movement and average airfare for the next 10-12 years to come. Thus, the study recommends that stakeholders in the air transport sector should work towards improving the capacity and infrastructure to accommodate the growth of air travel demand for domestic air travel in Nigeria. Policy implications were made on how to regulate the sector by having a good pricing policy to control the air fare for the industry.

Road transportation does an excellent job of connecting Savar's inner and outer areas, but it might be difficult for commuters to decide which mode of transportation to employ because residents of Savar come from a wide range of socioeconomic backgrounds. It is necessary to do in-depth research on the characteristics of people in the study region who choose different modes of transportation to achieve the goal of selecting a certain mode for their travel. Where a person lives can have a significant impact on their typical patterns of travel behavior. People who live closer to the center of things have access to a wider variety of amenities than those who live further away, and as a consequence, their travel patterns are distinct from one another. The study's findings indicate that several factors, including income, age, gender, and vocational qualities and goals, influence a commuter's preferred method of transportation. When it comes to selecting a mode of transportation, the most predictable factors to take into account are trip time and cost. After conducting research, it was found that most excursions are made from this place to Motijheel, Tejgaon, and Savar Export Processing Zone for their services, businesses, and jobs, respectively.

Snow removal and deicing using snowplow trucks assist transportation agencies to enhance roadway safety and mobility. However, due to slower travel speeds during these operations, motorists often end up in crashes for poor visibility and disturbance of the snow. Despite the risk associated with snowplows, no previous study was found that exclusively investigate the factors associated with injury severity in snowplow-involved crashes. Therefore, this paper presents an extensive exploratory analysis and fills this knowledge gap by identifying the significant contributing factors affecting the occupant injury severity from the aspects of crashes with snowplow involvement. The study utilized eleven years (2010-2020) of historical snowplow-related crash data from Wyoming. Both the binary logit model and mixed binary logit model were developed to investigate the impacts of the various occupant, vehicle, crash, roadway, and environmental characteristics on the corresponding occupant injury severity. As one of the important findings from this research concludes that other vehicle drivers are more responsible than snowplow drivers contributing to more severe injuries in crashes involving snowplows. Recommendations suggested based on the modeling results are expected to help transportation agencies and policymakers take necessary actions in reducing snowplow-involved crashes by targeting appropriate strategies and proper resource allocation.

The global world and individual countries, which are influenced by the economic, financial crises, and pandemics that occur in one way or another, have a major impact on business and its performance. Declining consumption, disrupted settlements, limited or unavailable sources of finance, and other economic and financial reasons may cause business failures. Efficient and rational financial management is crucial for companies to survive and operate successfully under various conditions of the economic cycle, especially in times of crisis. It can be argued that, under modern conditions of market economy, making economically sound decisions about the structure of funding sources is one of the most important tasks for business companies, since the formation of a capital structure establishes the company's ability to maximise its return, manage risks effectively, and operate successfully in a competitive environment to meet the needs of a wide range of stakeholders. The maritime sector is strategically important and economically significant for any country. Companies in this sector make a significant socio-economic contribution across the entire state. When forming the capital structure in the maritime sector companies, certain exceptions are encountered since the operation of these companies requires a large amount of borrowed capital. Increasing the business value of maritime sector companies has a positive meaning nationally and internationally.

This study uses TruckSim^TM to model disc brakes and drum brakes on a fully loaded truck semi-trailer to study the performance of each brake type as downgrades and speeds vary. The brake performance is measured based on braking distance. A simplified economic comparison based on life cycle cost analysis to determine which road and vehicle conditions give rise to the cost-effectiveness of disc brakes is performed. The studies suggest that disc brakes shorten braking distances by 10-20%. They also suggest that the percentage reduction in braking distance as speed increases and downgrade gets steeper is approximately 12-19%. Evidence is provided that trucking companies operating their vehicles in steep terrain and at high speeds with disc brakes could benefit from 12-80% in long-term cost savings. Finally, at the societal level, by preventing crashes arising from rear-end collisions and runaway truck incidents, disc brakes save at least $649 million annually.

Truck crashes on steep downgrades due to excessive brake heating, resulting from brake applications to control speeding, are a continuing cause of concern for the Wyoming Department of Transportation (WYDOT). In 2016, WYDOT funded a project to update the existing Grade Severity Rating System. Furthermore, in 2020, WYDOT commissioned a research project to automate the updated version of the mathematical model through an interactive, intuitive, aesthetically appealing and user-friendly Visual Basic.net objected-oriented software to simplify the computation of the maximum safe descent speed on these downgrades based on the truck weight. The software provides functionality for both the continuous Slope and separate downgrade methods. The primary beneficiaries of this software will be the highway agencies who will be able to estimate the maximum safe speed of descent for trucks with various weight categories and hence produce Weight Specific Speed (WSS) signs for each downgrade or a multigrade section.

Random parameter logit regression is used to analyze police-reported data on 8,253 heavy vehicle-related crashes in Addis Ababa between July 2014 and June 2017. The analysis shows that fatal crashes are more likely to occur during the day and on weekdays, particularly when the circulation of trucks is high. It also shows the disproportionately high involvement of young drivers in heavy vehicle crashes in the city. However, the likelihood of crashes resulting in fatalities and serious injuries increases slightly compared to those resulting only in property damage as the age of drivers increases. Low levels of drivers' education, the fact that drivers are often not the owners of vehicles, ownership of vehicles by companies and government organizations, and inappropriate road medians' inappropriate design are also significant contributors to fatal crashes. Curbing deaths and injuries from heavy vehicle crashes in Addis Ababa requires strict enforcement of traffic rules and regulations, particularly speed limits; reforms in driver's training and certification; improved safety culture of vehicle owners and design of road infrastructure. Ethiopia's national road safety strategy launched in July 2022 addresses these issues. Hence the government is taking steps in the right direction.

This study is focused on the influence that artificial intelligence can bring on warehouse performance. A sample of 329 workers from selected warehouses was used for this study, and a self-administered questionnaire was used to collect data. An index was constructed using the Principal Component Analysis (PCA) method to measure the influence on warehouse performance. Mann Whitney U test and Kruskal-Wallis H test were used to determine the effect of demographic factors on warehouse performance. The association among the variables was identified by employing correlation analysis. A regression analysis was performed to determine the relationship between the identified factors and warehouse performance. When the study tests for the association among the variables, it depicts a positive correlation. Finally, based on the analysis, it illustrates the influence of machine learning, robotics, the Internet of things (IoT), and fuzzy logic on warehouse performance. The warehouse performance was mentioned in three categories: time, inventory, and cost.

In highly competitive shipping market environment, container network operators-Freight forwarders, shipping companies etc. are concerned about design, development and deployment of optimized allocation model to achieve cost savings through improved container storage yard operations, crane productivity, outbound container allocation/distribution to seaport terminals and hence reduction in ships’ waiting times. In this paper, we developed two models, the Dynamic programming model and optimal allocation policy (model), for the optimal allocation of units of outbound laden cargo containers of sizes: 20ft and 40ft to six (6) major seaports in Nigeria. The distributions of the laden containers were allocated as follows: Port-Harcourt, Tincan Island, Onne, and Calabar seaports were allocated with 1,064 units of stuffed containers each. Apapa seaport was allocated with 2,128 units of laden containers, and zero allocation was made to Warri seaport. These results were arrived at through the implementation of the optimal allocation policy. The zero units allocation made to Warri seaport could be attributed to poor shipper patronage and hence the low frequency of ship visits. Apapa seaport was allocated double the number of containers moved to the remaining ports because it attracted more shipper patronage and hence more ship visits. Hence, freight forwarding companies will be assured of cargo spaces and make more profit by allocating more containers. Policy implications of the developed models were discussed.