Strava Metro data for bicycle monitoring: a literature review

ABSTRACT

Monitoring bicycle trips is no longer limited to traditional sources, such as travel surveys and counts. Strava, a popular fitness tracker, continuously collects human movement trajectories, and its commercial data service, Strava Metro, has enriched bicycle research opportunities over the last five years. Accrued knowledge from colleagues who have already utilised Strava Metro data can be valuable for those seeking expanded monitoring options. To convey such knowledge, this paper synthesises a data overview, extensive literature review on how the data have been applied to deal with drivers’ bicycle-related issues, and implications for future work. The review results indicate that Strava Metro data have the potential—although finite—to be used to identify various travel patterns, estimate travel demand, analyse route choice, control for exposure in crash models, and assess air pollution exposure. However, several challenges, such as the under-representativeness of the general population, bias towards and away from certain groups, and lack of demographic and trip details at the individual level, prevent researchers from depending entirely on the new data source. Cross-use with other sources and validation of reliability with official data could enhance the potentiality.     

The value of options for time charterparty extension: an artificial neural networks (ANN) approach

The most frequently associated options in the physical shipping market are options to extend the charter period on time charters and additional shipment options on contracts of affreightment. The value of freight options, in practice, is estimated mostly by referring to forward curves. An option on freight has different properties from its financial counterparts, and the straightforward adoption of theoretical models does not produce promising results. In this paper, extension options, which have the property of options on futures, were transformed into regular European options before the application of the Black-Scholes model (BSM). The efficient market hypothesis, which justifies the parity of the performance of a long-term charter to that of repetitive short-term charters, worked as the basis for the transformation. The option values determined by the BSM were compared with actual realized values. Additionally, the artificial neural networks (ANN) was employed to derive the option values. This study is meaningful as the first-time application of both the closed-form solution and the ANN to the valuation of physical freight options. The research results can contribute to the quality of chartering decisions. The results could also be used in quantifying credit risk, as extension options tend to be granted to charterers with more creditability.     

Effect of nozzle orifice diameter on diesel spray tip penetration according to various spray models for CFD simulation with widely varying back pressure

CFD simulations of spray tip penetration with the standard KIVA3V, ‘original gas jet’ and ‘Normal gas jet profile with breakup length formula’ (NGJBL) spray models were performed to investigate the effects of nozzle orifice size and ambient gas density combinations on the spray penetration. The accuracy of the CFD simulation results was estimated by comparing them with available experimental data. The ambient gas density was varied in 12 kg/m³ intervals from 12 to 69 kg/m³ for each nozzle orifice diameter. The nozzle orifice diameters used were 119, 140, 183 and 206 mm. A total of 20 cases in the CFD simulations were considered with combinations of the 4 nozzle orifice diameters and 5 ambient gas densities. CFD simulations with the NGJBL spray model were more accurate than those with either the standard KIVA3V or gas jet spray models as the nozzle orifice diameter and ambient gas density was increased. The NGJBL and original gas jet model is more effective in predicting the spray tip penetration near the nozzle tip region.     

Development of knowledge based body structure concept design model

The purpose of this study is to propose a concept design process for an automotive body structure using technical information on the major joints and members of vehicles. First, in order to collect the technical information on major joints and members, 17 vehicles were selected using benchmark data. The collected technical information for the selected vehicles was the cross sectional shapes of each joint and member which were used for the analysis of joint stiffness, crashworthiness and static stiffness of the member to make a database along with cross section properties. This study applied a ‘What If Study’ technique to perform a concept design of an automotive body using the analyzed information and selected cross section meeting the design objectives. The criteria for the selection of the cross section were defined by subdividing the defined design objectives of an automotive body structure and constraints into members and joints. In order to configure an analysis model of an automotive body structure using the selected cross section, a shape parametric model was used and static stiffness, dynamic stiffness and crashworthiness were assessed to evaluate the configured automotive body structure. The evaluation result showed that the crashworthiness and static/dynamic stiffness were improved compared to an existing body structure. In addition, the weight of the body structure was reduced. Through this study, the process that can rapidly and effectively derive and evaluate the concept design of an automotive body structure was defined. It is expected that, henceforth, this process will be helpful for the study of automotive body structures.     

Comparison of fuel efficiency and exhaust emissions between the aged and new DPF systems of Euro 5 diesel passenger car

This study was conducted to examine the impact of aged and new DPF systems of the Euro 5 diesel passenger car on fuel efficiency and exhaust emissions. Test diesel vehicle used in this study was equipped with diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) as aftertreatment systems, and satisfied the Euro-5 emissions standard. The displacement volume of engine was 1.6 L and the cumulative mileage was 167,068 km before the test. The FTP-75 test procedure was used, and the time resolved and weight based exhaust emissions of total hydrocarbon (THC), carbon monoxide (CO) and nitrogen oxides (NOx) were measured. The results show that the vehicle with the new DPF system has lower emissions of THC, CO and NOx than the aged one, and fuel efficiency also increased about 5 percent. The aged DPF system had higher backpressure due to the particulate matter (mostly in the form of ash) accumulated in the DPF. As was shown in the analysis using X-CT (X-ray computer tomography), the aged DPF system had particulate matter (PM) accumulated to a length of 46.6 mm. In addition, a component analysis of PM through XRF (X-ray fluorescence) analysis found that 50 % or more of the components consisted of the P, S, Ca, and Zn.     

Nanoparticle emission characteristics and reduction strategies by boost pressure control and injection strategies in a passenger diesel engine

This research attempted to analyze nanoparticles and other harmful exhaust emissions in accordance with injection strategies and air-fuel ratio (AFR) changes for small diesel engines. The emission characteristics were analyzed in the medium-speed condition, which is the main driving range of a diesel engine. In the case of particulate matter (PM), the number of particles was measured, analyzed, and compared to identify the correlation and emission characteristics of nanoparticles by using a dilution device and condensation particle counter (CPC), which are international standards for particle measurement recommended by the Particulate Measurement Programme (PMP). The engine torque tended to be reduced as pilot injections were added, and the torque was increased by the increased boost pressure, but reduced by the exhaust pressure increase in a part of the low-load range. The number of nanoparticles was not influenced greatly by the change in AFR, but the reduction effect on the PM weight was great depending on the boost pressure increase. In addition, the number of nanoparticles tended to increase as the fuel injection timing became closer to TDC in all conditions, and its difference became larger with an increase in AFR. In addition, in the case of the pilot injection, nanoparticle emission showed similar characteristics depending on the main injection timing, but it was increased by advanced injection timing when performing the main injection only, and the number of the nanoparticles increased as pilot injections were added. Last, the optimal conditions for EMS calibration were analyzed by selecting the conditions of torque reduction and NOx increase within 5 % from all of the engine operating conditions; optimized conditions are presented.     

Vibration reduction of H/Shaft using an electromagnetic damper with mode change

The objective of this study is to develop a damper that can reduce the amplitude of vibration in various frequency ranges. Previous H/Shaft vibration reduction methods work in a passive way. A dynamic damper reduces the amplitude of vibration at its first mode, but vibration still appears at the second mode. A mass damper or hollow shaft can shift the natural frequency to a lower or higher region. The fixed operating frequency prevents vibration from being reduced outside the operating frequency range. The proposed damper uses electromagnets as either masses or actuators to change the damper mode between dynamic damper mode and mass damper mode. The electromagnetic damper (EMD) can change its mode to respond to the vibration excitation at both low and high frequencies. The vibration reduction performance was evaluated by FRF tests in laboratory and vehicle conditions. The results were compared with those of a dynamic damper and indicate that the amplitude of vibration is reduced by 95.6 % when the EMD is implemented on an H/Shaft, whereas only 61.9 % vibration reduction is achieved by the dynamic damper.     

An analysis of destination choice for opaque airline products using multidimensional binary logit models

We investigate how customers respond to an opaque airline product offered by a European carrier. In this opaque product design, customers are randomly assigned to travel to one of approximately ten destinations; however, for a fee they may exclude one or more destinations from the choice set (or a particular package design) prior to learning which destination they will travel to. We use a multidimensional binary logit model to predict the probability that one or more alternatives will be chosen by a customer. Results show that customers are more likely to pay to exclude destinations located close to the origin airport and destinations that speak the same language as the origin airport. Length of stay, cost of living at the destination, and measures of destination attractiveness are also found to be significant predictors for some package designs. Based on these findings, we offer general recommendations for how to design opaque packages for airline customers.     

An advanced risk analysis approach for container port safety evaluation

Risk analysis in seaports plays an increasingly important role in ensuring port operation reliability, maritime transportation safety and supply chain distribution resilience. However, the task is not straightforward given the challenges, including that port safety is affected by multiple factors related to design, installation, operation and maintenance and that traditional risk assessment methods such as quantitative risk analysis cannot sufficiently address uncertainty in failure data. This paper develops an advanced Failure Mode and Effects Analysis (FMEA) approach through incorporating Fuzzy Rule-Based Bayesian Networks (FRBN) to evaluate the criticality of the hazardous events (HEs) in a container terminal. The rational use of the Degrees of Belief (DoB) in a fuzzy rule base (FRB) facilitates the implementation of the new method in Container Terminal Risk Evaluation (CTRE) in practice. Compared to conventional FMEA methods, the new approach integrates FRB and BN in a complementary manner, in which the former provides a realistic and flexible way to describe input failure information while the latter allows easy updating of risk estimation results and facilitates real-time safety evaluation and dynamic risk-based decision support in container terminals. The proposed approach can also be tailored for wider application in other engineering and management systems, especially when instant risk ranking is required by the stakeholders to measure, predict and improve their system safety and reliability performance.