Search results

The objective of this study is to investigate the impact of longitudinal forces on extreme-long heavy-haul trains, providing new insights and methods for their design and operation, thereby enhancing safety, operational efficiency and track system design.

A longitudinal dynamics simulation model of the super long heavy haul train was established and verified by the braking test data of 30,000 t heavy-haul combination train on the long and steep down grade of Daqing Line. The simulation model was used to analyze the influence of factors on the longitudinal force of super long heavy haul train.

Under normal conditions, the formation length of extreme-long heavy-haul combined train has a small effect on the maximum longitudinal coupler force under full service braking and emergency braking on the straight line. The slope difference of the long and steep down grade has a great impact on the maximum longitudinal coupler force of the extreme-long heavy-haul trains. Under the condition that the longitudinal force does not exceed the safety limit of 2,250 kN under full service braking at the speed of 60 km/h the maximum allowable slope difference of long and steep down grade for 40,000 t super long heavy-haul combined trains is 13‰, and that of 100,000 t is only 5‰.

The results will provide important theoretical basis and practical guidance for further improving the transportation efficiency and safety of extreme-long heavy-haul trains.

This paper aims to analyze the stress and strain distribution on the track wheel web surface and study the optimal strain gauge location for force measurement system of the track wheel.

Finite element method was employed to analyze the stress and strain distribution on the track wheel web surface under varying wheel-rail forces. Locations with minimal coupling interference between vertical and lateral forces were identified as suitable for strain gauge installation.

The results show that due to the track wheel web’s unique curved shape and wheel-rail force loading mechanism, both tensile and compressive states exit on the surface of the web. When vertical force is applied, Mises stress and strain are relatively high near the inner radius of 710 mm and the outer radius of 1110 mm of the web. Under lateral force, high Mises stress and strain are observed near the radius of 670 mm on the inner and outer sides of the web. As the wheel-rail force application point shifts laterally toward the outer side, the Mises stress and strain near the inner radius of 710 mm of the web gradually decrease under vertical force while gradually increasing near the outer radius of 1110 mm of the web. Under lateral force, the Mises stress and strain on the surface of the web remain relatively unchanged regardless of the wheel-rail force application point. Based on the analysis of stress and strain on the surface of the web under different wheel-rail forces, the inner radius of 870 mm is recommended as the optimal mounting location of strain gauges for measuring vertical force, while the inner radius of 1143 mm is suitable for measuring lateral force.

The research findings provide valuable insights for determining optimal strain gauge locations and designing an effective track wheel force measurement system.

In service, the periodic clashes of wheel flat against the rail result in large wheel/rail impact force and high-frequency vibration, leading to severe damage on the wheelset, rail and track structure. This study aims to analyze characteristics and dynamic impact law of wheel and rail caused by wheel flat of high-speed trains.

A full-scale high-speed wheel/rail interface test rig was used for the test of the dynamic impact of wheel/rail caused by wheel flat of high-speed train. With wheel flats of different lengths, widths and depths manually set around the rolling circle of the wheel tread, and wheel/rail dynamic impact tests to the flats in the speed range of 0–400 km/h on the rig were conducted.

As the speed goes up, the flat induced the maximum of the wheel/rail dynamic impact force increases rapidly before it reaches its limit at the speed of around 35 km/h. It then goes down gradually as the speed continues to grow. The impact of flat wheel on rail leads to 100–500 Hz middle-frequency vibration, and around 2,000 Hz and 6,000 Hz high-frequency vibration. In case of any wheel flat found during operation, the train speed shall be controlled according to the status of the flat and avoid the running speed of 20 km/h–80 km/h as much as possible.

The research can provide a new method to obtain the dynamic impact of wheel/rail caused by wheel flat by a full-scale high-speed wheel/rail interface test rig. The relations among the flat size, the running speed and the dynamic impact are hopefully of reference to the building of speed limits for HSR wheel flat of different degrees.

The purpose of this study is to examine supplier–customer capabilities in solution co-creation and how they are matched from a relational process perspective.

Using a qualitative approach, the authors identified 20 sets of supplier–customer capability matches by conducting in-depth interviews with 34 matched informants and retrieving suppliers’ archival data (project documents and success stories).

The authors identified 20 capability matching sets (21 supplier and 23 customer capabilities) and developed a process-based model of bilateral capabilities that match at the organizational level in solution co-creation. The authors reveal their match forms (complementarity and compatibility) and offer suggestions for future research.

This paper is qualitative; quantitative studies are required for testing and extending the initial conclusions.

This study guides the supplier and customer to cultivate different capabilities at different stages of solution co-creation and alerts them to the importance of capability complementarity and compatibility.

To the best of the authors’ knowledge, this study is the first to introduce the bilateral perspective into dynamic capability research in the context of solution co-creation. The authors discuss the abilities the supplier and customer must possess at different stages and how they match dynamically. The analysis extends the research on solution-specific capabilities and dynamic matching, offering useful implications for solution co-creation in practice.

While co-innovation with third parties (e.g. customer or supplier) has been widely documented, the literature seems to pay scant attention on co-innovation with business partners. Building on the resource dependence theory (RDT) and the input-process-output model, the purpose of this paper is to examine how four criteria of business partner selection affect service delivery co-innovation, which, in turn, influences firms’ competitive advantage.

A mail survey was sent to 600 IT service firms in Taiwan, the target respondents being senior marketing managers in charge of collaborative new service development. A total of 120 usable questionnaires were collected, for a response rate of 20 percent.

The findings support the argument that all four criteria of business partner selection have positive relationships with service delivery co-innovation. Meanwhile, adopting these criteria, firms’ service delivery co-innovation is able to create superior competitive advantage.

The findings enrich the existing literature by proposing and empirically confirming that the use of appropriate criteria to select business partners enhances the effectiveness of firms’ service delivery co-innovation and competitive advantage.

Managers must be aware of the criteria to select their business partners, in terms of developing service delivery co-innovation.

This study adds to the service innovation literature by providing support for the RDT that partner reliability, partner complementarity, partner expertise, and partner compatibility are important business partner selection criteria to create service delivery co-innovation and achieve firms’ competitive advantage.

This paper aims to build on the latest advances in cognitive computing techniques to systematically illustrate how unstructured data from users can offer significant value for co-innovation.

The paper adopts a general overview approach to understand how unstructured data from users can be analyzed with cognitive computing techniques for innovation. The paper links the computerized techniques with marketing innovation problems with an integrated framework using dynamic capabilities and complexity theory.

The paper identifies a suite of methodologies for facilitating company co-innovation via engaging with customers and external data with cognitive computing technologies. It helps to expand marketing researchers and practitioners’ understanding of using unstructured data.

This paper provides a conceptual framework that divides co-innovation process into three stages, ideas generation, ideas integration and ideas evaluation, and maps cognitive computing methodologies and technologies to each stage. This paper makes the theoretical contributions by developing propositions from both customer and firm perspectives.

This paper can be used for companies to engage consumers and external data for co-innovation activities by strategically select appropriate cognitive computing techniques to analyze unstructured data for better insights.

Given the lack of systematic discussion regarding what is possible from using cognitive computing to analyze unstructured data for co-innovation. This paper makes first attempt to summarize how unstructured data can be analyzed with cognitive computing techniques. This paper also integrates complexity theory to the framework from a novel perspective.