Modelling conical rock-bed solar thermal storage tank

An important application of solar thermal storage is for power generation or process heating. Low-temperature thermal storage in a packed rock bed is considered the best option for thermal storage for solar drying applications. In this chapter, mathematical formulations for conical have been developed. The model equations are solved numerically for charging/discharging cycles utilizing MATLAB. Results were compared with rock-bed storage with standard straight tank. From the simulated results, the temperature distribution was found to be more uniform in the truncated conical rock-bed storage. Also, the pressure drop over a long period of time in the conical thermal storage was as low as 25 Pa. Hence, the amount of power required from a centrifugal fan would be significantly lower. The flow of air inside the tank is simulated in SolidWorks software. From flow simulation, 3D modelling of flow is obtained to capture the actual scenario inside the tank.

Mathematical modelling of rock-bed solar thermal storage tank

An important application of thermal storage is solar energy for power generation or process heating. Low temperature thermal storage in a packed rock bed is considered best option for thermal storage for solar drying applications. In this paper, mathematical formulations for conical and cylindrical rock bed storage tanks have been developed. The model equations are solved numerically for charging/discharging cycles. From the simulated results, it was observed that for the same aspect ratio between the diameter and the length of the thermal storages, the conical thermal storage had better performance. The temperature distribution was found to be more uniform in the truncated conical shape rock bed storage. Also, the pressure drop over long period of time in the conical thermal storage was lower than that of the cylindrical thermal storage. Hence, the amount of power required from a centrifugal fan was lower.

Optimizing a piezometric network in the estimation of the groundwater budget: a case study from a crystalline-rock watershed in southern India

An estimate of the groundwater budget at the catchment scale is extremely important for the sustainable management of available water resources. Water resources are generally subjected to over-exploitation for agricultural and domestic purposes in agrarian economies like India. The double water-table fluctuation method is a reliable method for calculating the water budget in semi-arid crystalline rock areas. Extensive measurements of water levels from a dense network before and after the monsoon rainfall were made in a 53 km(2)atershed in southern India and various components of the water balance were then calculated. Later, water level data underwent geostatistical analyses to determine the priority and/or redundancy of each measurement point using a cross-validation method. An optimal network evolved from these analyses. The network was then used in re-calculation of the water-balance components. It was established that such an optimized network provides far fewer measurement points without considerably changing the conclusions regarding groundwater budget. This exercise is helpful in reducing the time and expenditure involved in exhaustive piezometric surveys and also in determining the water budget for large watersheds (watersheds greater than 50 km(2)).

Detecting drift from event streams of unpredictable business processes

Existing business process drift detection methods do not work with event streams. As such, they are designed to detect inter-trace drifts only, i.e. drifts that occur between complete process executions (traces), as recorded in event logs. However, process drift may also occur during the execution of a process, and may impact ongoing executions. Existing methods either do not detect such intra-trace drifts, or detect them with a long delay. Moreover, they do not perform well with unpredictable processes, i.e. processes whose logs exhibit a high number of distinct executions to the total number of executions. We address these two issues by proposing a fully automated and scalable method for online detection of process drift from event streams. We perform statistical tests over distributions of behavioral relations between events, as observed in two adjacent windows of adaptive size, sliding along with the stream. An extensive evaluation on synthetic and real-life logs shows that our method is fast and accurate in the detection of typical change patterns, and performs significantly better than the state of the art.

ACE Research Vignette 049: How Do Business Founders Use Business Plans?

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepreneurship researchers. In this vignette Per Davidsson and Christophe Garonne examine the use of business planning among business start-ups.

ACE Research Vignette 051: How and Why is Small Business Managers’ Age Related To Business Growth?

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international entrepreneurship researchers. This vignette, written by Professor Hannes Zacher, Professor Michael M. Gielnik and Dr Antje Schmitt, reports findings on relationships between small business managers’ age, their focus on opportunities, and business growth (sales and number of employees) over five years.

ACE Research Vignette #52: Business growth and new initiatives in small and medium manufacturing enterprises from a design innovation program

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepreneurship researchers. This vignette, written by Dr Judy Matthews examines the effects of firm engagement with design innovation programs on entrepreneurial activities of small and medium enterprises.

A “business researcher” view on opportunities for psychology in entrepreneurship research

In this short essay I offer some “business researcher” advice on how to leverage a strong background in psychology when attempting to contribute to the maturing field of “entrepreneurship research”. Psychologists can benefit from within-discipline research, e.g. on emergence, small groups, fit, and expertise as well as method strengths in, e.g. experimentation, operationalisation of constructs, and multi-level modelling. However, achieving full leverage of these strengths requires a clear conceptualisation of “entrepreneurship” as well as insights into the challenges posed by the nature of this class of phenomena.

How small business managers’ age and focus on opportunities affect business growth: A mediated moderation growth model

Research on business growth has been criticized for methodological weaknesses. We present a mediated moderation growth model as a new methodological approach. We hypothesized that small business managers' age negatively affects business growth through focus on opportunities. We sampled 201 small business managers and obtained firm performance data over 5 years, resulting in 836 observations. Growth modeling showed systematic differences in firm performance trajectories. These differences could be explained by modeling focus on opportunities as a mediator of the relationship between small business managers' age and business growth. The study illustrates how mediation models can be tested using growth modeling.

Applicability of Statistical Learning Algorithms for Spatial Variability of Rock Depth

Two algorithms are outlined, each of which has interesting features for modeling of spatial variability of rock depth. In this paper, reduced level of rock at Bangalore, India, is arrived from the 652 boreholes data in the area covering 220 sqa <.km. Support vector machine (SVM) and relevance vector machine (RVM) have been utilized to predict the reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth. The support vector machine (SVM) that is firmly based on the theory of statistical learning theory uses regression technique by introducing epsilon-insensitive loss function has been adopted. RVM is a probabilistic model similar to the widespread SVM, but where the training takes place in a Bayesian framework. Prediction results show the ability of learning machine to build accurate models for spatial variability of rock depth with strong predictive capabilities. The paper also highlights the capability ofRVM over the SVM model.

A model Integrating the Facilities Management Process with the Building End User’s Business Process (ProFacil)

The ProFacil model is a generic process model defined as a framework model showing the links between the facilities management process and the building end user’s business process. The purpose of using the model is to support more detailed process modelling. The model has been developed using the IDEF0 modelling method. The ProFacil model describes business activities from the generalized point of view as management-, support-, and core processes and their relations. The model defines basic activities in the provision of a facility. Examples of these activities are “operate facilities”, “provide new facilities”, “provide re-build facilities”, “provide maintained facilities” and “perform dispose of facilities”. These are all generic activities providing a basis for a further specialisation of company specific FM activities and their tasks. A facilitator can establish a specialized process model using the ProFacil model and interacting with company experts to describe their company’s specific processes. These modelling seminars or interviews will be done in an informal way, supported by the high-level process model as a common reference.

Two Scenarios for How Scholarly Publishers Could Change Their Business Model to Open Access

The Internet has made possible the cost-effective dissemination of scientific journals in the form of electronic versions, usually in parallel with the printed versions. At the same time the electronic medium also makes possible totally new open access (OA) distribution models, funded by author charges, sponsorship, advertising, voluntary work, etc., where the end product is free in full text to the readers. Although more than 2,000 new OA journals have been founded in the last 15 years, the uptake of open access has been rather slow, with currently around 5% of all peer-reviewed articles published in OA journals. The slow growth can to a large extent be explained by the fact that open access has predominantly emerged via newly founded journals and startup publishers. Established journals and publishers have not had strong enough incentives to change their business models, and the commercial risks in doing so have been high. In this paper we outline and discuss two different scenarios for how scholarly publishers could change their operating model to open access. The first is based on an instantaneous change and the second on a gradual change. We propose a way to manage the gradual change by bundling traditional “big deal” licenses and author charges for opening access to individual articles.