5 resultados para Java Simulation Tools

em Dalarna University College Electronic Archive


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This paper presents the result from a case study at Scania on product development processes. The objective with the case study was to gather information on Scania’s product development process (PDP) including the use of CAD and simulation tools, and project work. The objective was also to find any deviations or different interpretations among the employees on the PDP. To gather the information, semi-structured tape-recorded interviews have been used to ensure that individual interpretations from the interviewees could be gathered. Scania uses a defined and structured PDP which facilitates concurrent and cross-functional work. The PDP is implemented and followed to various degrees. The newly employed personnel may have difficulties with communication, both to find and to give information. Although, newly graduated personnel may find it easier to adapt to changes, and also to use a structured process which they have studied at universities. It was also known during the case study that the PDP is a major support for the newly employed personnel, which in turn decreases the time to get into the same working process as the more experienced personnel. Employees with decades of experience know the right sources from which to both give and gather information. Also, the terminology and definitions in the product development process may not be used as intended. This makes it difficult for other project members or teams who need to interpret the information received. At the same time, the routines among the more experienced personnel, which have been set-up throughout the years, make them more inflexible in adapting changes. The findings in the case study as well as challenges with implementing the PDP are known to Scania and are a part of the continuing work with improvement.

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Energy auditing can be an important contribution for identification and assessment of energy conservation measures (ECMs) in buildings. Numerous tools and software have been developed, with varying degree of precision and complexity and different areas of use.   This paper evaluates PHPP as a versatile, easy-to-use energy auditing tool and gives examples of how it has been compared to a dynamic simulation tool, within the EU-project iNSPiRe. PHPP is a monthly balance energy calculation tool based on EN13790. It is intended for assisting the design of Passive Houses and energy renovation projects and as guidance in the choice of appropriate ECMs.   PHPP was compared against the transient simulation software TRNSYS for a single family house and a multi-family house. It should be mentioned that dynamic building simulations might strongly depend on the model assumptions and simplifications compared to reality, such as ideal heating or real heat emission system. Setting common boundary conditions for both PHPP and TRNSYS, the ideal heating and cooling loads and demands were compared on monthly and annual basis for seven European locations and buildings with different floor area, S/V ratio, U-values and glazed area of the external walls.   The results show that PHPP can be used to assess the heating demand of single-zone buildings and the reduction of heating demand with ECMs with good precision. The estimation of cooling demand is also acceptable if an appropriate shading factor is applied in PHPP. In general, PHPP intentionally overestimates heating and cooling loads, to be on the safe side for system sizing. Overall, the agreement with TRNSYS is better in cases with higher quality of the envelope as in cold climates and for good energy standards. As an energy auditing tool intended for pre-design it is a good, versatile and easy-to-use alternative to more complex simulation tools.

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Generalized linear mixed models are flexible tools for modeling non-normal data and are useful for accommodating overdispersion in Poisson regression models with random effects. Their main difficulty resides in the parameter estimation because there is no analytic solution for the maximization of the marginal likelihood. Many methods have been proposed for this purpose and many of them are implemented in software packages. The purpose of this study is to compare the performance of three different statistical principles - marginal likelihood, extended likelihood, Bayesian analysis-via simulation studies. Real data on contact wrestling are used for illustration.

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The aim of this report is to give an overview of the results of Work Package 5 “Engineering Tools”. In this workpackage numerical tools have been developed for all relevant CHCP systems in the PolySMART demonstration projects (WP3). First, existing simulation platforms have been described and specific characteristics have been identified. Several different simulation platforms are in principle appropriate for the needs in the PolySMART project. The result is an evaluation of available simulation and engineering tools for CHCP simulation, and an agreement upon a common simulation environment within the PolySMART project. Next, numerical models for components in the demonstration projects have been developed. These models are available to the PolySMART consortium. Of all modeled components an overall and detailed working principle is formulated, including a parameter list and (in some cases) a control strategy. Finally, for four CHCP systems in the PolySMART project, a system simulation model has been developed. For each system simulation a separate deliverable is available (D5.5b to D5.5e) These deliverables replace deliverable 5.4 ‘system models’. The numerical models for components and systems developed in the Polysmart project form a valuable basis for the component development and optimisation and for the system optimisation, both within and outside the project. Developers and researchers interested in more information about specific models can refer to the institutes and contact persons involved in the model development. 

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In this paper, dynamic simulation was used to compare the energy performance of three innovativeHVAC systems: (A) mechanical ventilation with heat recovery (MVHR) and micro heat pump, (B) exhaustventilation with exhaust air-to-water heat pump and ventilation radiators, and (C) exhaust ventilationwith air-to-water heat pump and ventilation radiators, to a reference system: (D) exhaust ventilation withair-to-water heat pump and panel radiators. System A was modelled in MATLAB Simulink and systems Band C in TRNSYS 17. The reference system was modelled in both tools, for comparison between the two.All systems were tested with a model of a renovated single family house for varying U-values, climates,infiltration and ventilation rates.It was found that A was the best system for lower heating demand, while for higher heating demandsystem B would be preferable. System C was better than the reference system, but not as good as A or B.The difference in energy consumption of the reference system was less than 2 kWh/(m2a) betweenSimulink and TRNSYS. This could be explained by the different ways of handling solar gains, but also bythe fact that the TRNSYS systems supplied slightly more than the ideal heating demand.