Flow errors

Flow Low mass flow indicated. Mass flow error. Transmitter zero shift. Measurement is high. Measurement error. Liquid droplets in gas. Static pressure change in gas. Free water in fluid. Pulsation in flow. Non-standard pipe runs. Install demister upstream heat gas upstream of sensor. Add pressure recording pen. Mount transmitter above taps. Add process pulsation damper. Estimate limits of error. 

A more difficult criterion to meet with flow markers is that the polymer samples not contain interferents that coelute with or very near the flow marker and either affect its retention time or the ability of the analyst to reproducibly identify the retention time of the peak. Water is a ubiquitous problem in nonaqueous GPC and, when using a refractive index detector, it can cause a variable magnitude, negative area peak that may coelute with certain choices of totally permeated flow markers. This variable area negative peak may alter the apparent position of the flow marker when the flow rate has actually been invariant, thereby causing the user to falsely adjust data to compensate for the flow error. Similar problems can occur with the elution of positive peaks that are not exactly identical in elution to the totally permeated flow marker. Species that often contribute to these problems are residual monomer, reactants, surfactants, by-products, or buffers from the synthesis of the polymer. 

Solvent degassing is needed because gas bubbles in the pump head can cause malfunctions (air-lock) or flow errors (low flow). Dissolved air often... 

Table 1. Elevation calculations for Hawaiian basalt flows. Error bars in measured elevation are 200 m (see text).

Theorem 6.1 (Existence of continuous and approximate flows. Error estimate)... 

The pressure derivatives found from equation (18.50) for Prior Transient Integration and (18.54) for Extended Prior Transient Integration were integrated using the Euler method. In each case the error was measured in terms of the sum of the squared flow errors, E, at time to ... 

The first few seconds of the transient see a reversal of the pressure gradient between nodes 2 and 3, leading to a change in direction for flow This has an adverse effect on the sum of the squared flow errors (as is shown in Figure 18.10), which reaches a maximum of about 3 X 10" kg /s at the point of flow reversal. However the error sum reduces subsequently to settle at a steady value of about 4.3 x 10 kg /s for the rest of the transient. 

The sum of the squared flow errors is a sensitive measure of error, especially in the vicinity of flow reversal. Table 18.4 compares the values of the intermediate pressures p2 and p found from integration... 

Figure 18.10 Sum of squared flow errors in worked example.

Time into transient (seconds) Method P2 (kPa) P 1 (kPa) Flow error, E (kg /s )... 

Figure 18.11 Sum of squared flow errors when a linear approximation is made to the flow function near flow reversal (equation 18.34).

Figure A2.4 Flow error versus frictional pressure loss in velocity heads, Kt, and pressure ratio, p /pi, for a diatomic gas, y = 1.4, where...

If gas mixtures with concentrations varied over several orders of magnitude are needed, dosing the gas must be carried out via several dosing tracks with different flow rates. As is the case with many other measuring and control instruments, a percent rate of error, e, is specified when using the MFC technique. As the value refers not to the actual but to the maximum flow rate of the MFC (Fs,MFC-max)> not a relative error but an absolute flow error (A I mfc... 

One question still remains Why do many identification number systems still use check digit schemes that do not catch all of the errors listed in Table 1.2 This is a good question for which I have no answer. However, it does motivate the need to adjust current schemes and to create new ones. All of the concepts introduced in this book can be applied to create sophisticated schemes that will catch most errors. This was demonstrated by the Verhoeff scheme. With the birth of new identification number systems and the existence of old and ineffective check digit schemes, innovative schemes must be developed to ensure that data and information continue to flow error-free. 

There are three reasons the complexity of boundary conditions and the aquifer medium, which will take water inflow errors. selecting the applicable formulas the Dupuit equation is the steady flow of groundwater, but using the analytical method to predict water inflow in mines, the drawdown range from tens of meters to several hundred meters, is not a slowly varying flow. errors from selecte impact radius, impact radius in mines is impossible symmetrical. 

ACCE Automatic Correction of Control Flow Errors... 

CED A Control-flow Error Detection through Assertions... 

The control path is defined as the decision logic of a processor. It is responsible for calculating the next instmction to be fetched and setting the internal flags, such as to command the ALU to sum or subtract, and a branch to be taken or not. The control path is mostly combinational, but since it has to cross the pipeline stages, also has sequential logic. The main difference between the control path and the data path is that an error in the control path will most likely lead to control flow errors, such as a branch being taken, when it should not have. Such control flow errors may cause an erroneous result in the end of the computation or even an infinite loop. 

In order to differentiate a control flow from a data flow error, we check the PC evolution and compare it with a golden module. In case of a mismatch, the fault is classified as a control flow effect. If not, it is classified as a data flow effect. In some cases, a fault with a data flow effect may cause a control flow effect. An example could be an error in a register used to decide whether a branch should be taken or not. In such cases, we consider it as a control flow effect. 

Among the most important solutions to detect data flow errors, there are a few techniques that exploit information and operation redundancies, such as Error Detection by Data Diversity and Duplicated Instmctions (ED" l) (OH 2002a), the transformation technique proposed in Chey net (2000) and Variables 1 (VARl), Variables 2 (VAR2), and Variables 3 (VAR3) techniques proposed in Azambuja (2011b). 

Techniques to detect data flow errors introduce overheads in memory (both program and data) and execution time, due to extra instmctions in the original code and variable and registers replicatioa On the other hand, results presented at Azambuja (2010a) have shown 100 % fault detection for all SEU and SET injected directly in... 

Software-based techniques to detect control flow errors differ from data flow because of one main reason, which is control flow techniques can be optimized. Data flow techniques always have to replicate data (registers, variables or memory positions) and compare it, while control flow techniques can analyze the code, comprehend it and optimize the replication and comparison. Most control flow techniques perform an analysis on the program s execution flow, divide the program irrto Basic Blocks (BB) and parse the program flow as a graph between different nodes (BBs). A BB is defined as a sequence of consecutive instmctions that are always executed sequentially, meaning that the control flow always enters a BB in the first instmctions and leaves at the end of it. 

CFCSS was proposed in 2002 to complement ED I in its fault detection rates. It presented a Global Signature Register (GSR) to keep track of the control flow. By assigning BB values to GSR, he was able to detect most control flow errors, but still had issues with BB identifiers sharing the same value (which also happens to CCA). 

In order to improve CEDA, Vemu (2007) proposed ACCE and ACCE with Duplication (ACCED). They use the same detection capabilities from CEDA, but improve it by allowing error correction. Despite being unable to mitigate all control flow errors, ACCE imposes low laterrcy for error correction with performance overhead of about 20%. The otdy issue that remains is that neither ACCE nor ar r software-based technique is able to detect intra-node control flow errors, or in other words, faults causing control flow errors inside the same BB. 

The PODER technique is the first novel hybrid technique presented in this book. It was initially based in the CCA technique and its two-element queue to keep track of the changes in the program s control flow, called BID and CFID. The technique aims at detecting a few types of control flow errors, such as (1) incorrect jumps to the beginning of a BB, (2) incorrect jumps inside the same BB, (3) incorrect jumps to unused memory addresses, and (4) control flow loops. It is important to mention that PODER cannot detect errors in branch instructions, where a path should have been taken, but was not taken, and vice versa. In order to do so, it must be combined with the Inverted Branches software-based technique, described previously in Sect. 4.3. 

The software-based side of PODER rehes on adding extra instractions into the original program code, so that it can send data to the hardware-module and, by doing so, control it. From the four types of control flow errors mentioned before that PODER aims at, the software-base side is responsible for protecting the system against incorrect jumps to the same BB (1) and incorrect jumps to the begitming of a BB (2). 

A jump to the beginning of a basic block is a real problem because of the fact that the initialization of a BB usually contains extra instructions for control flow error detection. In some cases, the first instraction of a BB resets the control flow assertion, which can lead to undetected errors. Because of that, the detection of control flow errors to the beginning of a BB is mandatory. 

The fact that each BID is a unique prime number combined with the fact that the CFID is the multiplication of the destination BBs BIDS, gives PODER an interesting characteristic the operation rest of division of the dequeued CFDD by the destination BB s BID always returns zero when the control flow graph is respected by the exeeution flow. When the value is different than zero, some control flow error happened, causing an incorrect transition in the program s execution flow. 

OCFCM itself is defined as a non-intrasive hardware module and therefore corrld be considered a pure hardware-based technique. Irrstead, OCFCM alone cannot achieve its main objective, which is detecting control flow errors. To do so, it has to be complemented by the Inverted Branches software-based technique (described in Sect. 4.3) and configured by the apphcation running in the processor. Because of these characteristics, it is considered as a hybrid farrlt tolerant technique, even if not as tightly coupled with the software-side as PODER. 

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