RAM model

If the receptor is within an area source, or if emission rates do not vary markedly from one area source to another over most of the simulation area, the narrow-plume hypothesis can be used to consider only the variation in emission rates from each area source in the alongwind direction. Calculations are made as if from a series of infinite crosswind line sources whose emission rate is assigned from the area source emission rate directly upwind of the receptor at the distance of the line source. The ATDL model (22) accomplishes this for ground-level area sources. The RAM model (8) does this for ground-level or elevated area sources. 

The urban RAM model was evaluated (52) using 1976 sulfur dioxide data from 13 monitoring locations in St. Louis on the basis of their second-highest once-a-year concentrations. The ratio of estimated to measured 3-h average concentrations was from 0.28 to 2.07, with a median of 0.74. Half of the values were between 0.61 and 1.11. For the 24-h average concentrations the ratios ranged from 0.18 to 2.31, with a median of 0.70. Half of the values were between 0.66 and 1.21. Thus, the urban RAM model generally underestimates concentrations by about 25%. 

The process reliability simulation VIP should be initiated in the feasibility phase (FEL-2) to produce a block-level RAM model. Based on the results of that model, a more detailed equipment-level RAM model should be developed starting in the definition phase (FEL-3). 

During adverse meteorological events the use of an interface module to model dispersion parameters can have the advantage to reduce forecast error effects on predicted concentrations. Anyway, further analysis showed that the discussed results are strongly dependent on the radiation scheme used by RAMS model. 

The magnetic properties of most of the amorphous rare earth-nickel compounds are similar to those of alloys in which the rare earths are combined with nonmagnetic metals since the Ni atoms do not carry a magnetic moment in these alloys for all but the highest Ni concentration. For alloys with a rare earth component having non-zero orbital moment the so-called RAM model proposed by Harris et al. (1973)... 

Spare parts and consumables list Equipment fabrication and testing reports Equipment drawings Equipment installation drawings RAM model study report Vendor manuals... 

Ferrer et al. (1978) found excellent agreement between the RAM model description and the high-field magnetization curves obtained by various authors on amorphous alloys in which rare earth elements are combined with non-magnetic metals. Values of the parameters D and obtained by fitting the experimental results obtained by Boucher (1977a,b), Boucher and Barbara (1979) and Ferrer et al. (1978), have been collected in table 3. 

The objective of the paper is to describe an analytical RAM-model approach, and a RAM tool that supports maintenance evaluations. A sub-objective is to prove validity of the RAM tool by applying RAM analyses to decisions in maintenance management, at strategic, tactical, and operational levels. 

An analytic RAM model has been developed for the availability assessments and decision situations described above. The model adapts both single-state and multi-state consequences of component/system failures. The FPSO system is modeUed by rehabhity block diagrams where each block represents a single component or a sub-system. Production availability figures of the sub-systems are estimated based on the system configuration. Finally, the total system availability is estimated. The component availabihties are calculated based on the component-failure rates and... 

The RAM model is composed of block diagrams consisting of a hierarchy of serial and parallel structures. Each component may have several states, and transition rates between states are assumed to be constant. 

To illustrate its usefulness, apphcations related to strategic-, tactical- and operational-maintenance decisions are described in the following case examples. The examples are based on the same system model. Each case includes a general description of the decision problem, an overview of the adapted RAM model and its input data, the results generated from the model, and finally, the imphcation of the results for the specific decision situation. 

The work faking place to establish a RAM model requires insight into main system configurations and system ftmctionahty, as well as necessary availability and maintainability data. As an example, a part of a gas compression system is shown below based on an extract from a process flow diagram. 

The following sections describe different applications of the RAM model based on these elements. 

The objective of the RAM model is to illustrate, in a quantitative manner, the effects of system aging on the yearly production availability for the FPSO over the contractual period. An example of results, shown in Fig. 4, represents availability figures given the operational demands and decided maintenance program, without any specific measures taken. Input data is based on generic failure rates and repair... 

In an operational context, there is a need to adjust and optimize existing maintenance programs. In order to facilitate this, one has to be specific on failure causes and mechanisms. A Failure Mode Effect and Criticality Assessment (FMECA) module has thus been included in the RAM tool. With the FMECA module in place, the ageing and downtime modelling are further improved compared to the basic RAM model in Section 5.1. Critical failures are split into different failure modes with the related Mean Time to Failures (MTTFs) and failure causes. A description of maintenance measures is linked to each of the failure modes. Information regarding the different cost elements of maintenance and operation are registered in the maintenance-planning module, or the Reliability Centred Maintenance (RCM) module. Interval optimisation for each of the preventive maintenance tasks is derived as the interval that produces the minimum total cost. 

Also keep in mind that analytical RAM models always calculate average values of the production availability for a given time period. The effect of extreme values that is picked from experience data may then be overlooked in order to trace the most relevant... 

As illustrated these performance models (RAM models) may be a powerful tool for decision support when assessing different concepts and solutions. However, the development of such models requires experience data such as failure frequencies for all the systems and components to be fed into the model. Thus, where novel technology is applied or where conventional technology is apphed in a new application the information required to construct these performance models may not be readily available. 

The STMT IT,INK model in the form of an S-function was generated by CAMPG automatically as shown in Fig. 11.49. The 4-way valve and ram model becomes a SIMULINK S-function block with the CAMPG-generated function underneath. 

A conprehensive product release process ensures that products are very mamre when released. Parallel to the comprehensive quality management process the safety process starts with general safety requirements which are checked for applicability and allocated to the project respectively. It continues with several tasks like performance of an Functional Hazard Assessment, production of an hardware RAM Modelling and Prediction Report and a Failure Modes, Effects and Criticality Analysis for a typical configuration and the use of the previously mentioned hazard checklist. Finally all issues of the product release checklist are to be fulfilled to get the official release. 

The mean-field treatment of the RAM-model (eq. 102) with interactions... 

While there is good agreement between the RAM model description and the magnetization obtained at high fields, serious deviations are found (fig. 103) in... 

An initialization test protocol is used to configure the ASIC for the test mode by providing certain initialization vectors. Note that an initialization test protocol can only be used when the RAM model is not a black box in Synopsys. Toggling the inputs of a black box will not result in any improvements in fault coverage. If the RAM model in the Synopsys library has setup/hold timing arcs between the data/address pins and the write/iead enable and RAM select pins, one must place a testjsolate attribute on it. Without a seMestJsolate on the RAM, check test will try to trace back the write/read enable and RAM select pins to infer a clock which may cause other DRC violations. 

In addition, the LDA, RGA and GRM are part of RAM model in decommissioning phase as shown in Figure 2 and such accuracy was demonstrated on Figure 7, Table 1 and 2. 

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