3-D numerical modeling of methane hydrate deposits

Within the German gas hydrate initiative SUGAR, we have developed a new tool for predicting the formation of sub-seafloor gas hydrate deposits. For this purpose, a new 2D/3D module simulating the biogenic generation of methane from organic material and the formation of gas hydrates has been added to the petroleum systems modeling software package PetroMod®. T ypically, PetroMod® simulates the thermogenic generation of multiple hydrocarbon components including oil and gas, their migration through geological strata, and finally predicts the oil and gas accumulation in suitable reservoir formations. We have extended PetroMod® to simulate gas hydrate accumulations in marine and permafrost environments by the implementation of algorithms describing (1) the physical, thermodynamic, and kinetic properties of gas hydrates; and (2) a kinetic continuum model for the microbially mediated, low temperature degradation of particulate organic carbon in sediments. Additionally, the temporal and spatial resolutions of PetroMod® were increased in order to simulate processes on time scales of hundreds of years and within decimeters of spatial extension. As a first test case for validating and improving the abilities of the new hydrate module, the petroleum systems model of the Alaska North Slope developed by IES (currently Shlumberger) and the USGS has been chosen. In this area, gas hydrates have been drilled in several wells, and a field test for hydrate production is planned for 2011/2012. The results of the simulation runs in PetroMod® predicting the thickness of the gas hydrate stability field, the generation and migration of biogenic and thermogenic methane gas, and its accumulation as gas hydrates will be shown during the conference. The predicted distribution of gas hydrates will be discussed in comparison to recent gas hydrate findings in the Alaska North Slope region

Usability evaluation of a prototype design tool for uncertainty propagation and sensitivity analysis

Software developments in the domain of building performance simulation (BPS) targeting the early design stages of a building need to address two points successfully to be adopted in design practice: (1) facilitating communication between multiple engineering disciplines and (2) the limited amount of design information. The authors consider the limited amount of design information available not as a limit but as a design uncertainty. To focus the designer’s attention the approach chosen here is to extend the capabilities of existing simulation tools with uncertainty and sensitivity analysis. The development of software goes as any product development through stages as design, synthesis and analysis and involves numerous design iterations. The analysis of the prototypical tool extension includes verification und usability evaluation. Whilst the verification of prototypical design tools is necessary to ensure the added analysis functionality is implemented correctly the usability evaluation is to ensure the proposed feature meets the demand of the potential user group. A heuristic usability evaluation was conducted with six expert practitioners using a paper prototype. The quantitative feedback to heuristics as design guidance, process integration, and application confirmed the potential of the tool extension to support design practice. The usability evaluation indicated that expert practitioners would encourage the use of uncertainty propagation and sensitivity analysis if tool extensions to BPS-tools were available. The experts assess uncertainty propagation and sensitivity analysis to add value by reducing the risk of technical design decisions and limiting the extent of design iterations

Uncertainty and sensitivity analysis for detailed design support

Nowadays, building performance simulation (BPS) is still primarily used for code compliance checking in the Netherlands whilst it could provide the user already useful design information by e.g. indicating design solutions or introducing uncertainty analysis (UA) and sensitivity analysis (SA). This paper summarizes results from an ongoing research introducing UA and SA in BPS. A case study is performed based on a hypothetical building which is part of an international test method for assessing the accuracy of BPS tools with respect to various building performance parameters. SA is accomplished via a freeware tool called Simlab. This is used as a pre- and postprocessor for the BPS software VA114. The SA is based on seven different input parameters, covering different categories like uncertainties in physical and design parameters as well as in boundary conditions. The sample matrix for the different input was generated with the Latin hypercube method. Results considering energy consumption (annual heating and cooling, peak loads) and thermal comfort (weight over- and underheating hours) are compared. The paper will finish with indicating how this research will be proceeded

Model uncertainty and sensitivity analysis for thermal comfort prediction

Building Performance Simulation (BPS) is poorly used to support informed decision making between different design options nor is it used for building and/ or system optimization. Currently BPS is only used for code compliance during the detailed design [Wilde, 2004]. The approach of this research by using an existing tool as initial prototype is rapid prototyping to make incremental improvement of BPS. This paper elaborates the above in more detail in particular by focusing on an uncertainty and sensitivity analysis for thermal comfort prediction. A case study is described to evaluate the necessity of the use of uncertainty and sensitivity analysis in BPS. For that purpose an in the Netherlands well-known and commonly-used simulation tool for the detailed design is chosen. Furthermore, a range of results reflecting the impact of UA and SA are presented

Adaptive thermal comfort explained by PMV

Predicted Mean Vote (PMV) is a well known example of a thermal comfort performance indicator. Alternative indicators have gained interest over the last decade. Developments are found in higher resolution indicators, applying, e.g. thermo-physiological models. The adaptive thermal comfort approach (ATC), applying the indoor operative temperature in relation to the outdoor air temperature as the main performance indicator, represents an example of a less complex indicator. A clear advantage of the latter is the relative simple comfort assessment in use and the perceptibility of the indicator. However, the heat balance approach has a larger flexibility and a wider applicability. In this paper the linkage between PMV and ATC is elaborated on by investigating the search space for PMV input parameters in relation to the ATC assessment. The results show that for a moderate maritime outdoor climate as in The Netherlands the PMV-approach is well able to explain the results derived from the ATC approach

The impact of future climate scenarios on decision making in building performance simulation: a case study

Expected climate change may turn into a key challenge for building designers in the 21st century [Homes et al. 2007].In response to this challenge simulation packages have started to provide future climate scenarios to predict the energy demands and thermal comfort in buildings. The need to make predictions for climate change scenarios is becoming increasingly important.This paper describes the integration of climate change scenarios in one of the building performance simulation tools, i.e. VA114, which is used extensively in the Netherlands. Based on the existing traditional reference year "De Bilt 64/65", NEN 5060:2008 released a new norm that introduces four new climate files for different types of climate adjustments. KNMI on the other hand assembled four different future scenarios for the expected climate change. The climate files from the NEN and the KNMI future scenarios have been combined in a future climate data analysis for usage within the targeted simulation software VA114. The paper describes a case study focusing on the impact that a climate scenario may have on a concrete design decision. The case study involves two HVAC system designs: (1) a conventional cooling/heating system and (2) a heating/ cooling storage system. Both options are simulated and compared. The impact of climate change is shown on energy use and thermal comfort. It is then shown how the climate scenarios (and their inherent uncertainties) impact the uncertainty in the outcomes and how these outcomes influence the choice between the design options. The conclusions of the paper highlight the relevance of different (uncertain) climate scenarios and the role they play in design decision making