How value is created through service has recently undergone massive changes. Centralized service provision with clear distinctions between service offerers and beneficiaries is increasingly being substituted by value creation within decentralized networks of distributed actors integrating digital resources. One of the drivers of this transformation is blockchain technology. Applying the lens of service-dominant logic and discussing examples of blockchain-based decentralized finance, we shed light on how properties of decentralized technology stimulate value creation in service ecosystems. With this conceptual research, we postulate five propositions of decentralized value creation along the axiomatic foundations of the service-dominant logic. We provide first definitions for decentralized service as well as decentralized service ecosystems. Thereby, we contribute with an extension of the service-dominant logic to the context of decentralized ecosystems. To our knowledge, this research is among the first to add to the growing literature on blockchain value creation from a service science perspective.
Denmark has set ambitious targets, to reduce emission with 70% by 2030 and become independent of fossil fuels by 2050. To achieve those targets, Denmark is planning to accelerate the de-carbonization of the power system, by replacing fossil fuel generation plants with renewable energy sources (RES). Offshore wind power will form the backbone of power generation in a decarbonized system. Already world leading in electric consumption share covered by wind power, Denmark plans to install an additional 6.8 GW of offshore wind by 2030, quadrupling the 1.7 GW already connected to the system.
Taking offspring in a problem of ship emission reduction by exhaust gas recirculation control for large diesel engines, an underlying generic estimation challenge is formulated as a problem of joint state and parameter estimation for a class of multiple-input single-output Hammerstein systems with first-order dynamics, sensor delay, and a bounded time-varying parameter in the nonlinear part. This brief suggests a novel scheme for this estimation problem that guarantees exponential convergence to an interval that depends on the sensitivity of the system. The system is allowed to be nonlinear, parameterized, and time dependent, which are characteristics of the industrial problem we study. The approach requires the input nonlinearity to be a sector nonlinearity in the time-varying parameter. Salient features of the approach include simplicity of design and implementation. The efficacy of the adaptive observer is shown on simulated cases, on tests with a large diesel engine on test bed, and on tests with a container vessel.
International shipping has been reported to account for 13% of global NOx emissions and 2.1% of global green house gas emissions. Recent restrictions of NOx emissions from marine vessels have led to the development of exhaust gas recirculation (EGR) for large two-stroke diesel engines. Meanwhile, the same engines have been downsized and derated to optimize fuel efficiency. The smaller engines reduce the possible vessel acceleration, and to counteract this, the engine controller must be improved to fully utilize the physical potential of the engine. A fuel index limiter based on air/fuel ratio was recently developed (Turbo, 2016), but as it does not account for EGR, accelerations lead to excessive exhaust smoke formation which could damage the engine when recirculated.
This paper presents two methods for extending a fuel index limiter function to EGR engines. The methods are validated through simulations with a mean-value engine model and on a vessel operating at sea. Validation tests compare combinations of the two index limiter methods, using either traditional PI control for the EGR loop or the recently developed fast adaptive feedforward EGR control (Nielsen et al., 2017a). The experiments show that the extended limiters reduce exhaust smoke formation during acceleration to a minimum, and that the suggested limiter, combined with adaptive feedforward EGR control, is able to maintain full engine acceleration capability. Sea tests with engine speed steps from 35 to 50 RPM, made peak exhaust opacity increase by only 5% points when using the proposed limiter, whereas it increased 70% points without the limiter.
This paper evaluates the influence of forecast horizon and observation fit on the robustness and performance of a specific freight rate forecast model used in the liner shipping industry. In the first stage of the research, a forecast model used to predict container freight rate development is presented by exploring the relationship between individual company’s rates and aggregated market rates, and thus assists in dealing with uncertainty and market volatility for a given business situation. In the second stage, a design of experiment approach is applied to highlight the influence of the forecast horizon and observation fit and their interactions on the forecast model’s performance. The results underline the complicated nature of creating a suitable forecast model by balancing business needs, a desire to fit a good model and achieve high accuracy. There is strong empirical evidence from this study; that a robust model is preferable, that overfitting is a true danger, and that a balance must be achieved between forecast horizon and the number of observations used to fit the model. In addition, methodological guidance has also been provided on how to test, design, and choose the superior model for business needs.
This article gives a review of techniques applied to make sea state estimation on the basis of measured responses on a ship. The general concept of the procedures is similar to that of a classical wave buoy, which exploits a linear assumption between waves and the associated motions. In the frequency domain, this assumption yields the mathematical relation between the measured motion spectra and the directional wave spectrum. The analogy between a buoy and a ship is clear, and the author has worked on this wave buoy analogy for about fifteen years. In the article, available techniques for shipboard sea state estimation are addressed, but with a focus on only the wave buoy analogy. Most of the existing work is based on methods established in the frequency domain but, to counteract disadvantages of the frequency-domain procedures, newer studies are working also on procedures formulated directly in the time domain. Sample results from several studies are included, and the main findings from these are mentioned.
This paper deals with uncertainty modelling of wave-vessel transfer functions used to calculate or predict wave-induced responses of a ship in a seaway. Although transfer functions, in theory, can be calculated to exactly reflect the behaviour of the ship when exposed to waves, uncertainty in input variables, notably speed, draft and relative wave heading, often compromises results. In this study, uncertainty modelling is applied to improve theoretically calculated
transfer functions, so they better fit the corresponding experimental, full-scale ones. Based on a vast amount of full-scale measurements data, it is shown that uncertainty modelling can be successfully used to improve accuracy (and reliability) of theoretical transfer functions.
Short-term variability of ship responses is investigated by cross-spectrum analysis. In a steady state condition, it is well known that a certain length of sampled data is required for stable results of the spectral analysis. However, the phase lag between responses, in terms of the phase angle of the cross-spectra, has not been discussed in detail. Using long stationary time series, the transition of amplitudes and relative phase angles of the cross-spectra has
been investigated by iterative analyzes with a few seconds of time shifting. In the results, the short-term variability of the relative phase angle was observed. In effect, the variability may compromise the accuracy of the wave buoy analogy.
In this paper, a novel configuration of a pumped thermal electricity storage system is proposed which can integrate excess thermal energy from different renewable thermal energy sources, e.g. concentrated solar power, waste heat and deep geothermal energy plants, as well as excess electricity from direct electricity generating renewable energy sources, e.g. solar photovoltaic and wind energy plants. The proposed configuration can also be used as a retrofit option to existing conventional fossil fuel-based power plants. A conventional two-tank sensible heat storage is used as a thermal energy storage system that can be charged using direct renewable thermal energy and using a heat pump utilizing excess electricity. Different discharging cycles, including a Joule–Brayton system and a conventional steam Rankine cycle system, can be used. The proposed system can achieve a higher capacity factor compared to those of stand-alone plants.
As a case study, a conventional two-tank molten salt-based thermal energy storage system integrating concentrated solar power, considering a heliostat system, and a solar photovoltaic plant is investigated. The overall operational strategy of the plant was developed and based on that annual simulations were performed for a selected configuration. The results of the case study suggest that for a given requirement of capacity factor, the final selection of the capacities of the solar photovoltaic plant, heat pump and heliostat field should be done based on the minimum levelized cost of energy. Moreover, for high capacity factor requirements, the proposed configuration is promising.
Sustainable biofuel supply chain is a key to sustainable manufacturing and the future of production. Greener production is now becoming an order qualifier for the global competition. Modeling biofuel supply chains that achieve economic, social, and environmental feasibility is a challenge. This article develops biofuel platform planning and optimization that unifies biofuel product, production process and networks design into an umbrella of sustainable supply chain planning. A design of biofuel supply chain networks under various production paths is considered. The modeling results show that an optimum region of composition ratio between rice straws and waste cooking oils can be set within the range from 0% to 50%. Bio-diesel is favored over ethanol by occupying over 40% of the total biofuel outputs. However, ethanol yield is 99.1% and therefore it is sufficient to be directly mixed with gasoline at final depots. In terms of social contribution, it is estimated that the supply chain contribution to the case country GDP is about 0.17%. Looking at the above statistics, future research on global economic impacts and competitiveness of biofuel production is suggested.