Test Case. 3: Field observations The ATSPM vendor shall conduct a visual inspection of system performance and/or functionality in the field. This visual confirmation will document how the system satisfies requirements associated with field-observed operations and/or functions.
Test Case. Reporting from IN-FIELD Emergency Responder (ER) at any phase of the emergency Reporting from IN-FIELD Emergency Responder at any phase of the emergency Test Type: Manual Status: Final
Test Case. Analyze progress of the mission Analyze progress of the mission Test Type: Manual
Test Case. Obtain suggestions provided by the DSS engine of the EMC triggered by reports or notification Obtain suggestions provided by the DSS engine of the EMC triggered by reports or notifications Test Type: Manual
Test Case. Validate notifications from the EMC Validate notifications from the EMC Test Type: Manual
Test Case. Blood Flow in a Cerebral Aneurysm Computational models based on the NSE have become a valuable tool for the study of blood flow problems due to their cost-effectiveness and flexibility with respect to in vitro experimental studies. They allow the analysis of blood flow dynamics in subject-specific vascular geometries and the controlled and reproducible assessment of the effect of experimental parameters such as heart rate, average flow rate, and flow conditions in the neighboring parts of the circulatory system. The image-based CFD pipeline for blood flow problems starts with the image of a part of the circulatory system (typically including one or more arteries) acquired with techniques such as magnetic resonance or 3-D rotational angiography. A geometric model of the vascular structures is extracted from the image by means of segmentation techniques (see e.g. [56]). Such methods aim at characterizing the shape of the vessels, by identifying the contour separating blood from other biological structures in the image. This yields the definition of a surface that represents the domain of interest in which blood flow is simulated. To this end, a three-dimensional mesh is built. The Navier–Xxxxxx equations are solved at some selected instants within the time interval of interest assuming that blood velocity or blood pressure are known on the boundary of the volume of interest. In particular, subject-specific measurements may be used to quantify the unknowns on the inlet and outlet sections of the vascular geometry, while blood velocity is assumed to be zero in contact with the vascular wall (no-slip condition). This information is used to prescribe boundary conditions, required for the solution of the differential problem. The time discretization is performed by a suitable approximation of time derivatives, using the value of the solution in the collocation instants. Among others possibilities, we use here Backward Difference Formulas (BDF) with an error proportional to the square of the distance between two consecutive instants (second order methods) [57, 58]. The model problem used in our experiment is the blood flow in an internal carotid artery affected by a saccular brain aneurysm. Aneurysms are localized dilations of the arterial wall, often in the form of a blood-filled sac. They may rupture causing severe brain damage and even death. Fluid dynamics is considered one of the method that may help predict the outcome of the disease [59]. We consider a subj...
Test Case. Hellisheidi geothermal power plant In a first test case, the “full” model is validated for Hellisheidi, a conventional combined heat and power plant in Iceland. The results of the “full” model are calculated using site-specific parameters for the Hellisheidi plant31, which are reported in Table 4. These results are compared with an LCA model that we developed for the same operation in the commercial LCA software Gabi; notably, the results of the LCA study implemented in Gabi and the underlying data were published in peer-reviewed journals23,24.
Test Case. United Downs Deep Geothermal Power (UDDGP) project In a second test case, we validate the “full” model for the UDDGP project. The results of the “full” model are calculated using site-specific parameter for UDDGP that were collected on site and that are reported in Table 6. As for the case of Helllisheidi, the results of the “full” model are compared with an LCA model that we developed in the commercial LCA software Gabi, which we published in peer reviewed journals32,33. The results of the comparison are reported in Table 7; they are similar to those obtained for the Hellisheidi plant: deviations between the “full” model and the model implemented in Gabi are lower than 25%. for most environmental categories; higher deviations (up to ~150%) are due to changes in the Ecoinvent database. In Summary, our analysis suggests that the “full’ model is reliable, within the limits of uncertainties expected for LCA studies.
Test Case. A NUMERICAL APPLICATION The scope of this section is the use of the proposed LCOE formula to establish the optimal contractual length and price for a VCPPA aimed to the creation of a 20 MW capacity new PV power plant. A basic assumption refers to the power plant total forecasted production that balance the total energy needs of multiple corporate buyers. The estimated total energy production- consumption is 28 GWh per year. The production profile refers to the annual average profile for the PV plant located in Southern Italy while the consumption profile refers to a non-residential user considering for simplicity that all the n-users have the same load profile. As mentioned, the proposed LCOE is a stochastic value, so to take any decision for the investment profitability and to establish the VCPPA contractual length and price, an LCOE sensitivity analysis is also performed.
